Triple

T14331846
Position Surface form Disambiguated ID Type / Status
Subject Herne E355366 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object HER
HER is the vehicle registration code assigned to the town of Herne in the German state of North Rhine-Westphalia.
E1093894 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: HER | Statement: [Herne, hasVehicleRegistrationCode, HER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HER
Context triple: [Herne, hasVehicleRegistrationCode, HER]
  • A. HER
    HER is the commonly used abbreviation for the Harvard Educational Review, a scholarly journal focused on education research and policy.
  • B. HER
    HER is the official herbarium code assigned to the Berggarten botanical collection, used in scientific and taxonomic references.
  • C. HER
    HER is a reinforcement learning technique that improves learning from sparse rewards by reinterpreting failed experiences as successful ones for alternative goals.
  • D. Her
    "Her" is a soulful R&B song by American singer-songwriter SiR, known for its smooth production and introspective lyrics about love and vulnerability.
  • E. Her
    Her is the standard three-letter IAU abbreviation for the northern constellation Hercules.
  • 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: HER
Triple: [Herne, hasVehicleRegistrationCode, HER]
Generated description
HER is the vehicle registration code assigned to the town of Herne in the German state of North Rhine-Westphalia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: HER
Target entity description: HER is the vehicle registration code assigned to the town of Herne in the German state of North Rhine-Westphalia.
  • A. HER
    HER is the commonly used abbreviation for the Harvard Educational Review, a scholarly journal focused on education research and policy.
  • B. HER
    HER is the official herbarium code assigned to the Berggarten botanical collection, used in scientific and taxonomic references.
  • C. HER
    HER is a reinforcement learning technique that improves learning from sparse rewards by reinterpreting failed experiences as successful ones for alternative goals.
  • D. Her
    Her is a 2013 science-fiction romantic drama film directed by Spike Jonze that explores a man's emotional relationship with an advanced artificial intelligence operating system.
  • E. Her
    "Her" is a lesser-known work by American poet, painter, and City Lights Books co-founder Lawrence Ferlinghetti, reflecting his characteristic Beat-influenced, avant-garde literary style.
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8c1fb87c81908412c2953243c8e3 completed April 14, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46943dac819092f5935d9d312949 completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd4811e2808190b559d8348079ae8f completed May 8, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69fd48d827488190b4a494d4da64ba51 completed May 8, 2026, 2:22 a.m.
Created at: April 10, 2026, 1:13 a.m.