Triple

T6146721
Position Surface form Disambiguated ID Type / Status
Subject Lutetia E137096 entity
Predicate locatedIn P40 FINISHED
Object modern-day Paris E568 NE FINISHED

How this triple was built (2 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: modern-day Paris | Statement: [Lutetia, locatedIn, modern-day Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: modern-day Paris
Context triple: [Lutetia, locatedIn, modern-day Paris]
  • A. central Paris
    Central Paris is the historic and cultural heart of France’s capital, encompassing its most famous landmarks, dense urban core, and major business, shopping, and tourist districts.
  • B. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • C. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • D. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • E. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cdeeaa88190948d9db6eb2dbf46 completed March 22, 2026, 9:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135fe8ae48190bfb20c335c7d32be completed March 23, 2026, 12:45 p.m.
Created at: March 22, 2026, 4:16 p.m.