Triple

T16736327
Position Surface form Disambiguated ID Type / Status
Subject Belchite offensive E406727 entity
Predicate location P40 FINISHED
Object Belchite E405328 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: Belchite | Statement: [Belchite offensive, location, Belchite]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belchite
Context triple: [Belchite offensive, location, Belchite]
  • A. Belchite chosen
    Belchite is a historic town in northeastern Spain best known for the ruins left by a devastating Spanish Civil War battle, preserved as a memorial to the conflict.
  • B. Ubaque
    Ubaque is a municipality in central Colombia known for its rural Andean landscapes and traditional agricultural communities.
  • C. Caleruega
    Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
  • D. Acesines
    Acesines is the ancient Greek name for the Chenab River, a major river of the Punjab region in South Asia.
  • E. Arganzuela
    Arganzuela is a central district of Madrid, Spain, known for its extensive redevelopment along the Manzanares River and its mix of residential areas, cultural venues, and green spaces.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e39c3a86848190a03f243dd1bdb899 completed April 18, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a51c5c388190a88f8bd67dbac82e completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:20 a.m.