Triple

T515562
Position Surface form Disambiguated ID Type / Status
Subject École Polytechnique E10698 entity
Predicate nickname P55 FINISHED
Object l’X
l’X is the traditional nickname of École Polytechnique, France’s elite engineering grande école renowned for its rigorous scientific education and prestigious alumni.
 E64254 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: l’X | Statement: [École Polytechnique, nickname, l’X]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: l’X
Context triple: [École Polytechnique, nickname, l’X]
  • A. 9X
    9X is the IATA airline designator assigned to Southern Airways Express, a U.S.-based regional commuter airline.
  • B. CX
    CX is the two-letter IATA airline designator used to identify Cathay Pacific in global aviation systems.
  • C. OX
    OX is the postcode area covering Oxford and its surrounding region in Oxfordshire, England.
  • D. X
    X is a company owned and controlled by X Corp., operating as its subsidiary within the same corporate group.
  • E. Lex
    Lex is a common shortened form of the given name Alexander, often used as a modern, informal nickname.
  • 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: l’X
Triple: [École Polytechnique, nickname, l’X]
Generated description
l’X is the traditional nickname of École Polytechnique, France’s elite engineering grande école renowned for its rigorous scientific education and prestigious alumni.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: l’X
Target entity description: l’X is the traditional nickname of École Polytechnique, France’s elite engineering grande école renowned for its rigorous scientific education and prestigious alumni.
  • A. 9X
    9X is the IATA airline designator assigned to Southern Airways Express, a U.S.-based regional commuter airline.
  • B. CX
    CX is the two-letter IATA airline designator used to identify Cathay Pacific in global aviation systems.
  • C. OX
    OX is the postcode area covering Oxford and its surrounding region in Oxfordshire, England.
  • D. X
    X is a company owned and controlled by X Corp., operating as its subsidiary within the same corporate group.
  • E. Lex
    Lex is a common shortened form of the given name Alexander, often used as a modern, informal nickname.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1836b688190a60cc901a8724159 completed Feb. 28, 2026, 1:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4a1508e7c8190983dfe0b87c6c7ca completed March 1, 2026, 8:28 p.m.
NEDg Description generation batch_69a4a222e4008190990842b744945f88 completed March 1, 2026, 8:31 p.m.
NED2 Entity disambiguation (via description) batch_69a4a27f91ec81909cb25a8e004632ef completed March 1, 2026, 8:33 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.