Triple

T3531704
Position Surface form Disambiguated ID Type / Status
Subject Southern France E74674 entity
Predicate includesCity P3207 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: [Southern France, includesCity, Carcassonne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carcassonne
Context triple: [Southern France, includesCity, 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9a14c881908932b17ed3eececb completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e9a2b848190a5c2b3072fa6c44c completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.