Triple

T11062166
Position Surface form Disambiguated ID Type / Status
Subject Badian E261532 entity
Predicate hasNearbyCity P350 FINISHED
Object Moalboal E235324 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: Moalboal | Statement: [Badian, hasNearbyCity, Moalboal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moalboal
Context triple: [Badian, hasNearbyCity, Moalboal]
  • A. Moalboal chosen
    Moalboal is a coastal town in the Philippines renowned for its vibrant coral reefs, sardine runs, and popular diving and snorkeling spots.
  • B. Guihulngan
    Guihulngan is a coastal city and commercial hub in the northern part of Negros Oriental in the Philippines.
  • C. Calbayog
    Calbayog is a coastal city in the province of Samar in the Philippines, known as a regional hub for trade, culture, and transportation in Eastern Visayas.
  • D. Malalag
    Malalag is a coastal municipality in the province of Davao del Sur in the Philippines, known for its fishing communities and access to Davao Gulf.
  • E. Pagbilao
    Pagbilao is a coastal municipality in the province of Quezon, Philippines, known for its power plant, beaches, and mangrove forests.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798eb838c819089a89c55209c0295 completed April 9, 2026, 12:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6037fdf80819091fb2c8bf128582d completed April 20, 2026, 10:44 a.m.
Created at: April 8, 2026, 9:26 p.m.