Triple

T11554941
Position Surface form Disambiguated ID Type / Status
Subject Province of Alicante E273993 entity
Predicate hasLargestCity P235 FINISHED
Object Alicante E326236 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: Alicante | Statement: [Province of Alicante, hasLargestCity, Alicante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alicante
Context triple: [Province of Alicante, hasLargestCity, Alicante]
  • A. Alicante chosen
    Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial center.
  • B. Alcoy
    Alcoy is an industrial and historically significant city in southeastern Spain, known for its textile heritage, modernist architecture, and famous Moors and Christians festival.
  • C. Valencia
    Valencia is a major Spanish coastal city known for its historic architecture, vibrant culture, and significant role as a key Mediterranean trade and tourism hub.
  • D. Valencia
    Valencia is a major inland city in the Philippine province of Bukidnon, known as a commercial and agricultural hub in Northern Mindanao.
  • E. Valencia
    Valencia is a city located in the highland province of Bukidnon in the Philippines, known as a major agricultural and commercial center in the region.
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88a86be308190973fea5d7db8ba9d completed April 10, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f416f5e0588190b432a48bbbc6c762 completed May 1, 2026, 2:59 a.m.
Created at: April 8, 2026, 9:37 p.m.