Triple

T3804606
Position Surface form Disambiguated ID Type / Status
Subject Samuel ibn Tibbon E91773 entity
Predicate placeOfBirth P1 FINISHED
Object Lunel E161071 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: Lunel | Statement: [Samuel ibn Tibbon, placeOfBirth, Lunel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lunel
Context triple: [Samuel ibn Tibbon, placeOfBirth, Lunel]
  • A. Lunel chosen
    Lunel is a commune in southern France known for its historic center and location between Montpellier and Nîmes in the Occitanie region.
  • B. La Grande-Motte
    La Grande-Motte is a seaside resort town on France’s Mediterranean coast, noted for its distinctive modernist pyramid-shaped architecture and beaches.
  • C. Le Cannet
    Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
  • D. Leucate
    Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
  • E. Blaye
    Blaye is a wine-producing area on the right bank of the Gironde estuary in southwestern France, known for its red and white Bordeaux wines and historic citadel.
  • 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7bc240881909e91b7b99403a13c completed March 9, 2026, 3:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f107148190bf7ce74eb7dee9b2 completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:15 p.m.