Triple

T13145631
Position Surface form Disambiguated ID Type / Status
Subject Enga Province E312327 entity
Predicate largestTown P235 FINISHED
Object Wabag E1024289 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: Wabag | Statement: [Enga Province, largestTown, Wabag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wabag
Context triple: [Enga Province, largestTown, Wabag]
  • A. Wabag chosen
    Wabag is a small highland town in Papua New Guinea that serves as the administrative and commercial center of Enga Province.
  • B. Itogon
    Itogon is a mountainous municipality in Benguet province in the Philippines, known for its mining industry and scenic river valleys.
  • C. Dingalan
    Dingalan is a coastal municipality in the province of Aurora, Philippines, known for its rugged mountains, scenic bays, and emerging eco-tourism attractions.
  • D. Kabuntalan
    Kabuntalan is a municipality in the province of Maguindanao del Norte in the Philippines, known for its location along the Rio Grande de Mindanao and its predominantly Maguindanaon population.
  • E. Bayambang
    Bayambang is a municipality in the province of Pangasinan in the Philippines, known for its agricultural economy and historical significance dating back to the Spanish colonial period.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bcf6d0c819081d078f33e4bdedc completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5d809948190aced5ce377402463 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 9:10 p.m.