Triple

T21578280
Position Surface form Disambiguated ID Type / Status
Subject Self-Employment Income Support Scheme E532456 entity
Predicate shortName P43 FINISHED
Object SEISS
SEISS is a UK government grant program introduced during the COVID-19 pandemic to provide financial support to self-employed individuals whose businesses were adversely affected.
 E1491200 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SEISS | Statement: [Self-Employment Income Support Scheme, shortName, SEISS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SEISS
Context triple: [Self-Employment Income Support Scheme, shortName, SEISS]
  • A. Sise
    Sise is a surname most notably associated with Charles Fleetford Sise, a prominent Canadian telecommunications executive and early leader of Bell Canada.
  • B. Sisebut
    Sisebut was an early 7th-century king of the Visigoths known for his military campaigns against the Byzantines in Hispania and his promotion of Christianity, including forced conversions of Jews.
  • C. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • D. SEBE
    SEBE is the commonly used acronym for the Faculty of Science, Engineering and Built Environment at Deakin University.
  • E. SÉG
    SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SEISS
Triple: [Self-Employment Income Support Scheme, shortName, SEISS]
Generated description
SEISS is a UK government grant program introduced during the COVID-19 pandemic to provide financial support to self-employed individuals whose businesses were adversely affected.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SEISS
Target entity description: SEISS is a UK government grant program introduced during the COVID-19 pandemic to provide financial support to self-employed individuals whose businesses were adversely affected.
  • A. Sise
    Sise is a surname most notably associated with Charles Fleetford Sise, a prominent Canadian telecommunications executive and early leader of Bell Canada.
  • B. Sisebut
    Sisebut was an early 7th-century king of the Visigoths known for his military campaigns against the Byzantines in Hispania and his promotion of Christianity, including forced conversions of Jews.
  • C. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • D. SEBE
    SEBE is the commonly used acronym for the Faculty of Science, Engineering and Built Environment at Deakin University.
  • E. SÉG
    SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0c4618bec8190bcb0feb74568cbb1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb5ac1048190aa45d7d3c780b5c9 completed April 27, 2026, 4:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09f67889bc81908d640cbe0bc4b121 completed May 17, 2026, 5:10 p.m.
NEDg Description generation batch_6a09f70d94308190b1c8f11e0a93b883 completed May 17, 2026, 5:12 p.m.
NED2 Entity disambiguation (via description) batch_6a09f7f91058819081d7230042ec080c completed May 17, 2026, 5:16 p.m.
Created at: April 16, 2026, 6:31 p.m.