Triple

T3541393
Position Surface form Disambiguated ID Type / Status
Subject Lingotto complex E74892 entity
Predicate locatedInDistrict P40 FINISHED
Object Lingotto E74892 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: Lingotto | Statement: [Lingotto complex, locatedInDistrict, Lingotto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lingotto
Context triple: [Lingotto complex, locatedInDistrict, Lingotto]
  • A. Schatz
    Schatz is a German-language surname borne by various individuals of German and Jewish heritage.
  • B. Orlandi Valuta
    Orlandi Valuta is a money transfer and financial services brand owned by Western Union, primarily serving customers in the United States and Latin America.
  • C. Tolar Grande
    Tolar Grande is a small remote village in Argentina’s Salta Province, known as a gateway to high-altitude Andean deserts and salt flats.
  • D. Lingotto complex chosen
    The Lingotto complex is a former Fiat automobile factory in Turin, Italy, transformed into a modern multi-purpose center featuring shops, hotels, a conference center, and the iconic rooftop test track.
  • E. Kassa
    Kassa is the historical Hungarian name for the city now known as Košice in eastern Slovakia.
  • 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_69ad85d274cc8190ab59c97298a1cfbf completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbf729000819086e4fdba9e73e198 completed March 8, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bda9b848190a06b4b7113f97fc1 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:20 p.m.