Triple

T17824429
Position Surface form Disambiguated ID Type / Status
Subject Cergy E445075 entity
Predicate hasEducationalInstitution P113 FINISHED
Object ENSEA
ENSEA is a French grande école of engineering specializing in electronics and related fields, located in Cergy.
E1289355 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: ENSEA | Statement: [Cergy, hasEducationalInstitution, ENSEA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ENSEA
Context triple: [Cergy, hasEducationalInstitution, ENSEA]
  • A. Ecomare
    Ecomare is a nature museum and seal sanctuary on the Dutch island of Texel that focuses on the Wadden Sea, North Sea, and regional marine wildlife and conservation.
  • B. Ekoi
    Ekoi are an ethnic group of southeastern Nigeria and western Cameroon known for their rich artistic traditions, especially elaborate masks and skin-covered sculptures.
  • C. SEAS
    SEAS is the acronym for Yale University's School of Engineering & Applied Science, which houses its engineering and applied science programs.
  • D. SEAS
    SEAS is the University of Pennsylvania’s engineering and applied science school, offering undergraduate and graduate programs in fields such as computer science, bioengineering, and mechanical engineering.
  • E. SEAS
    SEAS is the abbreviation for the Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University's engineering and applied sciences school.
  • 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: ENSEA
Triple: [Cergy, hasEducationalInstitution, ENSEA]
Generated description
ENSEA is a French grande école of engineering specializing in electronics and related fields, located in Cergy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ENSEA
Target entity description: ENSEA is a French grande école of engineering specializing in electronics and related fields, located in Cergy.
  • A. Ecomare
    Ecomare is a nature museum and seal sanctuary on the Dutch island of Texel that focuses on the Wadden Sea, North Sea, and regional marine wildlife and conservation.
  • B. Ekoi
    Ekoi are an ethnic group of southeastern Nigeria and western Cameroon known for their rich artistic traditions, especially elaborate masks and skin-covered sculptures.
  • C. SEAS
    SEAS is the acronym for Yale University's School of Engineering & Applied Science, which houses its engineering and applied science programs.
  • D. SEAS
    SEAS is the University of Pennsylvania’s engineering and applied science school, offering undergraduate and graduate programs in fields such as computer science, bioengineering, and mechanical engineering.
  • E. SEAS
    SEAS is the abbreviation for the Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University's engineering and applied sciences school.
  • 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4891352ac8190ad3d669fea1c9fbb completed April 19, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02ff69f02c81908a7b6b8b564cceec completed May 12, 2026, 10:22 a.m.
NEDg Description generation batch_6a03000abe908190a4f4835f348aa544 completed May 12, 2026, 10:25 a.m.
NED2 Entity disambiguation (via description) batch_6a0300e885e481909c76dfbac2fd1009 completed May 12, 2026, 10:28 a.m.
Created at: April 10, 2026, 10:15 a.m.