Triple

T13706127
Position Surface form Disambiguated ID Type / Status
Subject Naga Airport E328645 entity
Predicate servesArea P82 FINISHED
Object Naga metropolitan area E67022 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: Naga metropolitan area | Statement: [Naga Airport, servesArea, Naga metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naga metropolitan area
Context triple: [Naga Airport, servesArea, Naga metropolitan area]
  • A. Naga City chosen
    Naga City is a major urban center in the Bicol Region of the Philippines, known as a cultural, religious, and educational hub.
  • B. Naga City
    Naga City is a component city in the province of Cebu in the Philippines, known for its industrial activities and coastal location in the central Visayas region.
  • C. Butuan City
    Butuan City is a highly urbanized and historically significant city in the Caraga region of Mindanao in the Philippines, known as a commercial hub and an important archaeological and cultural center.
  • D. Gaya city
    Gaya city is a major urban center in the Indian state of Bihar, renowned as a Hindu pilgrimage site near the Buddhist holy city of Bodh Gaya.
  • E. Mau city
    Mau city is an urban center in the Indian state of Uttar Pradesh known for serving as the administrative and commercial hub of Mau district.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dcad17732c8190bbd0d73107711c99 completed April 13, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7945b63288190819621830ac1c0d6 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:54 p.m.