Triple

T9079046
Position Surface form Disambiguated ID Type / Status
Subject Silver Airways E217566 entity
Predicate ICAOCode P419 FINISHED
Object SIL
SIL is the ICAO airline designator assigned to Silver Airways, a U.S.-based regional airline.
 E776251 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: SIL | Statement: [Silver Airways, ICAOCode, SIL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SIL
Context triple: [Silver Airways, ICAOCode, SIL]
  • A. SILE
    SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
  • B. SILJU
    SILJU is the UN/LOCODE designation for the city and transport hub of Ljubljana, the capital of Slovenia.
  • C. SL
    SL is the public transport authority and brand responsible for operating and coordinating the mass transit system in the Stockholm region of Sweden.
  • D. SL
    SL is a German vehicle registration code used on license plates to identify cars registered in the Saalekreis district of Saxony-Anhalt.
  • E. SL
    SL is a mid-range trim level of the Vauxhall Viva that added extra comfort and cosmetic features over the base model.
  • 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: SIL
Triple: [Silver Airways, ICAOCode, SIL]
Generated description
SIL is the ICAO airline designator assigned to Silver Airways, a U.S.-based regional airline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SIL
Target entity description: SIL is the ICAO airline designator assigned to Silver Airways, a U.S.-based regional airline.
  • A. SILE
    SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
  • B. SILJU
    SILJU is the UN/LOCODE designation for the city and transport hub of Ljubljana, the capital of Slovenia.
  • C. SL
    SL is the public transport authority and brand responsible for operating and coordinating the mass transit system in the Stockholm region of Sweden.
  • D. SL
    SL is a German vehicle registration code used on license plates to identify cars registered in the Saalekreis district of Saxony-Anhalt.
  • E. SL
    SL is a mid-range trim level of the Vauxhall Viva that added extra comfort and cosmetic features over the base model.
  • 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc95c93ee48190842623b57e50f4cf completed April 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffe2103448190bbc09436f19c4f11 completed April 3, 2026, 5:51 p.m.
NEDg Description generation batch_69d000d4a4548190939a9a9946be469b completed April 3, 2026, 6:03 p.m.
NED2 Entity disambiguation (via description) batch_69d001b245f08190a8e5c53c570b20a0 completed April 3, 2026, 6:06 p.m.
Created at: March 30, 2026, 7:12 p.m.