Triple

T515555
Position Surface form Disambiguated ID Type / Status
Subject École Polytechnique E10698 entity
Predicate previousLocation P13839 FINISHED
Object Paris E568 NE FINISHED

How this triple was built (3 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: Paris | Statement: [École Polytechnique, previousLocation, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [École Polytechnique, previousLocation, Paris]
  • A. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • C. Rouen
    Rouen is a historic city in northern France renowned for its medieval architecture, Gothic cathedral, and association with figures like Joan of Arc and the Impressionist painter Claude Monet.
  • D. Toulouse
    Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
  • E. Strasbourg
    Strasbourg is a major French city on the Rhine known for hosting key European institutions, including the European Parliament and the Council of Europe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: previousLocation
Context triple: [École Polytechnique, previousLocation, Paris]
  • A. previousMeetingPlace
    Indicates the location where two or more entities met on a prior occasion.
  • B. previousGround
    Indicates that one entity is the immediately preceding ground or surface state relative to another in a sequence or progression.
  • C. previousVenue chosen
    Indicates that one venue was used or occupied before another in a sequence of venues.
  • D. currentLocationSince
    Indicates the point in time since which an entity has been at its current location.
  • E. previousVersionLocationOfAdoption
    Indicates that one entity is the location where an earlier or prior version of another entity was adopted.
  • F. None of above.

Provenance (4 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_69a2f232fa688190b08a2fe3f22c7a6e completed Feb. 28, 2026, 1:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e023ac5c8190b0233471d1d4eece completed March 2, 2026, 12:56 a.m.
PD Predicate disambiguation batch_69a2f013c05481909e6dc87e7b20ebd8 completed Feb. 28, 2026, 1:39 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.