Triple

T1261653
Position Surface form Disambiguated ID Type / Status
Subject Paris–Lausanne railway E12514 entity
Predicate hasEndpointCity P26386 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: [Paris–Lausanne railway, hasEndpointCity, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Paris–Lausanne railway, hasEndpointCity, 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. 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.
  • C. 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.
  • D. Palaiseau
    Palaiseau is a suburban commune in the southern outskirts of Paris, France, known for hosting major scientific and engineering institutions.
  • E. 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.
  • 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: hasEndpointCity
Context triple: [Paris–Lausanne railway, hasEndpointCity, Paris]
  • A. hasTargetCity
    Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
  • B. hasPortCity
    Indicates that a place or region possesses or is associated with a city that functions as its port.
  • C. coversCity
    Indicates that one entity extends over, includes, or geographically encompasses the area of a specified city.
  • D. hasCityPair
    Indicates a relationship that links two cities considered as a connected or associated pair, often for purposes such as travel, trade, or comparison.
  • E. isInCity
    Indicates that one entity is located within the geographical boundaries of a specified city.
  • 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_69a4933352e08190ac617291985e76c0 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bfc64e648190b9c4f980eb8168aa completed March 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc61df4b48190aa142f30026e6580 completed March 8, 2026, 12:43 a.m.
PD Predicate disambiguation batch_69a4bb6eefbc81908dddd7d2ef368186 completed March 1, 2026, 10:19 p.m.
PDg Predicate description generation batch_69a4bd98b62c8190a5f6710345c0537d completed March 1, 2026, 10:28 p.m.
Created at: March 1, 2026, 7:50 p.m.