Triple

T23267105
Position Surface form Disambiguated ID Type / Status
Subject Runway 13L/31R E588181 entity
Predicate servesCity P82 FINISHED
Object San Antonio NE NERFINISHED

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: San Antonio | Statement: [Runway 13L/31R, servesCity, San Antonio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Antonio
Context triple: [Runway 13L/31R, servesCity, San Antonio]
  • A. San Antonio chosen
    San Antonio is a large, historic city in south-central Texas known for the Alamo, the River Walk, and its rich blend of Mexican and Texan culture.
  • B. San Antonio
    San Antonio is a coastal municipality in the province of Northern Samar in the Philippines, known for its island beaches and fishing communities.
  • C. San Antonio
    San Antonio is a coastal municipality in the Philippine province of Zambales known for its beaches, coves, and nearby island-hopping destinations.
  • D. San Antonio
    San Antonio is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • E. San Antonio
    San Antonio is a barangay (village-level administrative division) within the municipality of Capul in the Philippines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e25d148adc819088efbf42672604e9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f194cd13b48190a9c282545a34f348 completed April 29, 2026, 5:19 a.m.
Created at: April 17, 2026, 4:38 p.m.