Triple

T18736006
Position Surface form Disambiguated ID Type / Status
Subject Herrenberg E458163 entity
Predicate twinTown P1072 FINISHED
Object Péronne NE NERFINISHED

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: Péronne | Statement: [Herrenberg, twinTown, Péronne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Péronne
Context triple: [Herrenberg, twinTown, Péronne]
  • A. Péronne chosen
    Péronne is a historic town in northern France known for its role in World War I and its location in the Somme department.
  • B. Saint-Valery-sur-Somme
    Saint-Valery-sur-Somme is a historic coastal town in northern France, known for its picturesque setting on the Baie de Somme and its well-preserved medieval architecture.
  • C. Landrecies
    Landrecies is a small commune in northern France, historically part of the fortified border region of French Flanders.
  • D. Neufchâtel-sur-Aisne
    Neufchâtel-sur-Aisne is a small commune in northern France situated along the Aisne River.
  • E. Arras
    Arras is a historic city in northern France renowned for its Flemish-Baroque architecture, grand squares, and role as a strategic site in both World Wars.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d7ae10081908bc6857d1d147eef completed April 20, 2026, 12:04 a.m.
Created at: April 10, 2026, 11:51 a.m.