Triple

T13679233
Position Surface form Disambiguated ID Type / Status
Subject Bordeaux–Sète railway E327954 entity
Predicate serves P98 FINISHED
Object Carcassonne E90283 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: Carcassonne | Statement: [Bordeaux–Sète railway, serves, Carcassonne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carcassonne
Context triple: [Bordeaux–Sète railway, serves, Carcassonne]
  • A. Carcassonne chosen
    Carcassonne is a historic fortified city in southern France renowned for its medieval citadel with double walls and numerous watchtowers.
  • B. Cité
    Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
  • C. Crevel
    Crevel is a vain, wealthy former perfumer and libertine in Honoré de Balzac’s novel "La Cousine Bette," emblematic of the corrupt bourgeois society he satirizes.
  • D. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • E. Cour Carrée
    Cour Carrée is the large, historic square courtyard at the eastern end of the Louvre in Paris, surrounded by classical palace façades that reflect the museum’s origins as a royal residence.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66cbb088190907cb89dda8e4ebd completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944347a08190bc1386e78ddb3e71 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.