Triple

T2950951
Position Surface form Disambiguated ID Type / Status
Subject Bataan World War II Museum (Balanga) E79817 entity
Predicate locatedIn P40 FINISHED
Object Balanga E254766 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: Balanga | Statement: [Bataan World War II Museum (Balanga), locatedIn, Balanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balanga
Context triple: [Bataan World War II Museum (Balanga), locatedIn, Balanga]
  • A. Balanga chosen
    Balanga is a coastal city in the province of Bataan in the Philippines, situated along the shores of Manila Bay.
  • B. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • C. Aguiguan
    Aguiguan is a small, uninhabited island in the Northern Mariana Islands known for its rugged terrain and seabird colonies.
  • D. Palimbang
    Palimbang is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing communities and Moro cultural heritage.
  • E. Malungon
    Malungon is a landlocked agricultural municipality in the province of South Cotabato in the Philippines, known for its hilly terrain and farming-based economy.
  • 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98fbb7d4819081c241f3ff9165e5 completed March 8, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc7edc808190863ec8f99efa3875 completed March 11, 2026, 5:24 a.m.
Created at: March 8, 2026, 2:57 p.m.