Triple

T15995029
Position Surface form Disambiguated ID Type / Status
Subject Hénon metro station E387939 entity
Predicate hasStationCode P1289 FINISHED
Object HEN
HEN is the station code for Hénon metro station on the Lyon Metro system in France.
 E1188527 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: HEN | Statement: [Hénon metro station, hasStationCode, HEN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HEN
Context triple: [Hénon metro station, hasStationCode, HEN]
  • A. HE
    HE is the Faculty of Health at Aarhus University, responsible for education and research in medical and health sciences.
  • B. EH
    EH is the ISO 3166-1 alpha-2 country code assigned to Western Sahara.
  • C. EH
    EH is the postcode area covering Edinburgh and surrounding parts of eastern Scotland.
  • D. EH
    EH is the IATA airline designator assigned to ANA Wings, a regional subsidiary of All Nippon Airways in Japan.
  • E. HEL
    HEL is the three-letter IATA airport code for Helsinki Airport, the main international gateway to Finland’s capital region.
  • 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: HEN
Triple: [Hénon metro station, hasStationCode, HEN]
Generated description
HEN is the station code for Hénon metro station on the Lyon Metro system in France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HEN
Target entity description: HEN is the station code for Hénon metro station on the Lyon Metro system in France.
  • A. HE
    HE is the Faculty of Health at Aarhus University, responsible for education and research in medical and health sciences.
  • B. EH
    EH is the postcode area covering Edinburgh and surrounding parts of eastern Scotland.
  • C. EH
    EH is the IATA airline designator assigned to ANA Wings, a regional subsidiary of All Nippon Airways in Japan.
  • D. EH
    EH is the ISO 3166-1 alpha-2 country code assigned to Western Sahara.
  • E. HEL
    HEL is the three-letter IATA airport code for Helsinki Airport, the main international gateway to Finland’s capital region.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15785fad48190af0556e7ddfd29c5 completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3d5d72081908aa235c5ad9b5707 completed May 9, 2026, 11:31 p.m.
NEDg Description generation batch_69ffc5444c1c8190854de5575b9ec1c5 completed May 9, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69ffc5b95290819098b28c44c22b2799 completed May 9, 2026, 11:39 p.m.
Created at: April 10, 2026, 4:55 a.m.