Triple

T11554907
Position Surface form Disambiguated ID Type / Status
Subject Province of Alicante E273993 entity
Predicate contains P35 FINISHED
Object city of 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: city of Alicante | Statement: [Province of Alicante, contains, city of Alicante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Alicante
Context triple: [Province of Alicante, contains, city of 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. City of Yecla
    The City of Yecla is a historic Spanish municipality in the Region of Murcia, noted for its wine production, furniture industry, and archaeological heritage.
  • C. Orihuela
    Orihuela is a historic city in southeastern Spain known for its rich medieval heritage, religious architecture, and role as a regional cultural center.
  • D. 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.
  • E. Valencia
    Valencia is a municipality in the Philippine province of Negros Oriental known for its cool climate, geothermal energy resources, and natural attractions such as waterfalls and mountain landscapes.
  • 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_69e6e865c3008190bc2f04a1048f2fed completed April 21, 2026, 3 a.m.
Created at: April 8, 2026, 9:37 p.m.