Triple

T15728705
Position Surface form Disambiguated ID Type / Status
Subject Abbé Faujas E381284 entity
Predicate arrivesIn P49364 FINISHED
Object Plassans E345390 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: Plassans | Statement: [Abbé Faujas, arrivesIn, Plassans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plassans
Context triple: [Abbé Faujas, arrivesIn, Plassans]
  • A. Plassans chosen
    Plassans is a fictional provincial town in southern France created by Émile Zola as a central setting in several of his Rougon-Macquart novels.
  • B. Lessebo
    Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
  • C. Paute
    Paute is a small town in southern Ecuador known for its agricultural production and scenic Andean valley setting.
  • D. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • E. Karlaplan
    Karlaplan is a prominent circular plaza and park with a central fountain in the Östermalm district of Stockholm, Sweden.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb4cc0081909efe330339474017 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82faa5508190a28e2a224d4a4a06 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:46 a.m.