Triple

T14415561
Position Surface form Disambiguated ID Type / Status
Subject Pully E357440 entity
Predicate hasTwinTown P919 FINISHED
Object Obernai E245096 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: Obernai | Statement: [Pully, hasTwinTown, Obernai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Obernai
Context triple: [Pully, hasTwinTown, Obernai]
  • A. Obernai chosen
    Obernai is a historic Alsatian town in northeastern France known for its well-preserved medieval architecture, wine production, and picturesque setting along the Alsace Wine Route.
  • B. Sarrebourg
    Sarrebourg is a small historic town in northeastern France known for its cultural heritage and location in the Moselle department of the Grand Est region.
  • C. Mondorf-les-Bains
    Mondorf-les-Bains is a spa town in southeastern Luxembourg renowned for its thermal baths, wellness facilities, and casino.
  • D. Berg-sur-Moselle
    Berg-sur-Moselle is a small French commune in the Moselle department of northeastern France, near the border with Luxembourg.
  • E. Sarreguemines
    Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90cc99208190a2313b1acfb5d802 completed April 14, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64e68118819082448393cc141d96 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:17 a.m.