Triple

T6775169
Position Surface form Disambiguated ID Type / Status
Subject Maguindanaon people E155137 entity
Predicate historicalCenters P45017 FINISHED
Object Lambayong E285579 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: Lambayong | Statement: [Maguindanaon people, historicalCenters, Lambayong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lambayong
Context triple: [Maguindanaon people, historicalCenters, Lambayong]
  • A. Lambayong chosen
    Lambayong is a municipality in the province of Sultan Kudarat in the Philippines, known for its predominantly agricultural economy and rural communities.
  • B. Balgüe
    Balgüe is a small rural village on Ometepe Island in Lake Nicaragua, known for its scenic setting near volcanic landscapes and eco-tourism lodges.
  • C. Soreang
    Soreang is a suburban district and the administrative center of Bandung Regency in West Java, Indonesia, situated within the greater Bandung metropolitan area.
  • D. Taebong
    Taebong was a short-lived Korean kingdom of the early 10th century that emerged during the Later Three Kingdoms period before being absorbed by Goryeo.
  • E. Sokcho
    Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
  • 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_69c68812ef7c819099369f51febb725c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7c94bac8190ae4b236d1b04bec9 completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a803fe08190b4dc32d09e91da07 completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:13 p.m.