Triple

T4719975
Position Surface form Disambiguated ID Type / Status
Subject Negros Island E104739 entity
Predicate hasCity P316 FINISHED
Object Guihulngan E335670 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: Guihulngan | Statement: [Negros Island, hasCity, Guihulngan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guihulngan
Context triple: [Negros Island, hasCity, Guihulngan]
  • A. Guihulngan chosen
    Guihulngan is a coastal city and commercial hub in the northern part of Negros Oriental in the Philippines.
  • B. Moalboal
    Moalboal is a coastal town in the Philippines renowned for its vibrant coral reefs, sardine runs, and popular diving and snorkeling spots.
  • C. Sagay
    Sagay is a coastal city in the province of Negros Occidental in the Philippines, known for its rich marine resources and protected seascape.
  • D. 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.
  • E. Calapan
    Calapan is the capital city of Oriental Mindoro in the Philippines, serving as a key commercial and transportation hub in the Mimaropa region.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6428e9e081908ce4041183cad13b completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07d33a65481908c7ab4473bed1320 completed March 22, 2026, 11:37 p.m.
Created at: March 20, 2026, 1:18 p.m.