Triple

T15408241
Position Surface form Disambiguated ID Type / Status
Subject Ariège department E368518 entity
Predicate contains P35 FINISHED
Object Pamiers E94688 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: Pamiers | Statement: [Ariège department, contains, Pamiers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pamiers
Context triple: [Ariège department, contains, Pamiers]
  • A. Pamiers chosen
    Pamiers is a historic commune in southwestern France, known as the largest town in the Ariège department and noted for its medieval architecture and role as a local economic center.
  • B. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • C. Perejaume
    Perejaume is a contemporary Catalan artist and poet known for his conceptual explorations of landscape, language, and the relationship between art and territory.
  • D. Jachenau
    Jachenau is a small Bavarian municipality in southern Germany, known for its scenic alpine landscape and traditional rural character.
  • E. Sierpc
    Sierpc is a historic town in central Poland known for its traditional wooden architecture and open-air museum showcasing Mazovian rural culture.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ea36c6881909eaea48e9608897a completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a716248819094fd8b205cc2a3f2 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:20 a.m.