Triple

T5291146
Position Surface form Disambiguated ID Type / Status
Subject Vålerenga Fotball E119743 entity
Predicate nickname P55 FINISHED
Object Enga E119743 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: Enga | Statement: [Vålerenga Fotball, nickname, Enga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Enga
Context triple: [Vålerenga Fotball, nickname, Enga]
  • A. Enga chosen
    Enga is the popular nickname of Vålerenga Fotball, a prominent Oslo-based Norwegian football club known for its passionate supporters.
  • B. Oshiwambo
    Oshiwambo is a Bantu language (or cluster of closely related dialects) widely spoken by the Ovambo people in northern Namibia and southern Angola.
  • C. Ilala
    Ilala is a central administrative district of Dar es Salaam in Tanzania, encompassing key commercial, residential, and transport hubs of the city.
  • D. Saarang
    Saarang is the annual cultural festival of IIT Madras, known as one of India’s largest and most prominent college cultural fests featuring music, arts, literary, and performing arts events.
  • E. Angangueo
    Angangueo is a historic mining town in central Mexico best known as a gateway to the Monarch Butterfly Biosphere Reserve.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eccac481908ba3fe28c3908d1d completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10dfc2948190b65f5e4c9388a5cb completed March 21, 2026, 9:42 p.m.
Created at: March 20, 2026, 1:52 p.m.