Triple

T11315625
Position Surface form Disambiguated ID Type / Status
Subject Genk E267956 entity
Predicate hasTwinTown P919 FINISHED
Object Tata E516832 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: Tata | Statement: [Genk, hasTwinTown, Tata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tata
Context triple: [Genk, hasTwinTown, Tata]
  • A. Tata
    Tata is a small town and oasis in southern Morocco, known as a gateway to the Anti-Atlas mountains and the surrounding desert landscapes.
  • B. Tata
    Tata is the nickname of Gerardo "Tata" Martino, an Argentine football manager and former player known for coaching top clubs and national teams, including FC Barcelona, Argentina, and Mexico.
  • C. Tata chosen
    Tata is a historic Hungarian town in Komárom-Esztergom County known for its lakes, castles, and natural surroundings.
  • D. Tata
    Tata is a prominent Indian industrial and philanthropic family best known for founding and leading the multinational conglomerate Tata Group.
  • E. Tata Motors
    Tata Motors is a major Indian multinational automotive manufacturer known for producing a wide range of passenger and commercial vehicles and for owning the luxury car brand Jaguar Land Rover.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c2c7b081909af8acebc8aa93aa completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a9e66588190b71e0f60133a8995 completed April 19, 2026, 5:02 p.m.
Created at: April 8, 2026, 9:32 p.m.