Triple

T12787774
Position Surface form Disambiguated ID Type / Status
Subject Oullins E305675 entity
Predicate hasTwinTown P919 FINISHED
Object Pescia E812641 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: Pescia | Statement: [Oullins, hasTwinTown, Pescia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pescia
Context triple: [Oullins, hasTwinTown, Pescia]
  • A. Pescia chosen
    Pescia is a historic Tuscan town in central Italy known for its paper production, floriculture, and medieval architecture.
  • B. Sarzana
    Sarzana is a historic town in the Liguria region of northwestern Italy, known for its medieval fortifications and strategic position near the border with Tuscany.
  • C. Peccioli
    Peccioli is a historic hilltop town in Tuscany, Italy, known for its medieval architecture, cultural initiatives, and innovative waste-to-energy and contemporary art projects.
  • D. Pisogne
    Pisogne is a picturesque town in northern Italy’s Lombardy region, known as a lakeside resort and historic gateway to the Val Camonica area.
  • E. Luino
    Luino is a town in northern Italy’s Lombardy region, known for its lakeside setting near the Swiss border and its historic weekly market.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5dbdb88190a1b06721ada51627 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af4bd22c819091050e5a40a4a96a completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:29 p.m.