Triple

T10257539
Position Surface form Disambiguated ID Type / Status
Subject Têt River E240510 entity
Predicate passesThrough P225 FINISHED
Object Prades E152411 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: Prades | Statement: [Têt River, passesThrough, Prades]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prades
Context triple: [Têt River, passesThrough, Prades]
  • A. Prades chosen
    Prades is a small town in southern France known for its picturesque setting in the Pyrenees and its cultural and historical heritage.
  • B. Desnos
    Desnos is the surname of Robert Desnos, a notable French surrealist poet and member of the Resistance during World War II.
  • C. Bonnieux
    Bonnieux is a picturesque hilltop village in southeastern France’s Provence region, known for its historic stone houses, terraced streets, and panoramic views over the Luberon valley.
  • D. Lacanau
    Lacanau is a coastal resort town in southwestern France known for its Atlantic beaches, surfing, and large freshwater lake.
  • E. Camprodon
    Camprodon is a small town in the Catalan Pyrenees of northeastern Spain, known for its scenic mountain setting and historic Romanesque architecture.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24de4588190b68fb3daa36dbd7d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7e153b0819084708b6f7127cdea completed April 9, 2026, 12:50 a.m.
Created at: April 6, 2026, 11:31 a.m.