Triple

T1162402
Position Surface form Disambiguated ID Type / Status
Subject Touraine E24522 entity
Predicate containsCity P294 FINISHED
Object Tours E41188 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: Tours | Statement: [Touraine, containsCity, Tours]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tours
Context triple: [Touraine, containsCity, Tours]
  • A. Tours chosen
    Tours is a historic city in central France’s Loire Valley, known for its medieval old town, proximity to famous châteaux, and role as a regional transport and cultural hub.
  • B. Tours, France
    Tours, France is a historic city in the Loire Valley known for its medieval old town, Renaissance architecture, and role as a cultural and economic center of central France.
  • C. Tour Voile
    Tour Voile is a prominent annual offshore sailing race in France featuring multihull and monohull competitions along the French coastline.
  • D. Wikivoyage
    Wikivoyage is a free, collaboratively edited online travel guide that provides up-to-date information and tips for destinations around the world.
  • E. Universal Destinations & Experiences
    Universal Destinations & Experiences is the theme park and resort division of NBCUniversal that develops and operates Universal-branded entertainment destinations worldwide.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcb2bb84819088bd94e91c10fb0c completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f15a9ac8190802f66f3699fbbe7 completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:45 p.m.