Triple

T4242279
Position Surface form Disambiguated ID Type / Status
Subject Sierra Madre E95440 entity
Predicate province P604 FINISHED
Object Quezon E188573 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: Quezon | Statement: [Sierra Madre, province, Quezon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quezon
Context triple: [Sierra Madre, province, Quezon]
  • A. Quezon chosen
    Quezon is a province in the Philippines located in the Calabarzon region on the island of Luzon, known for its coconut plantations, cultural festivals, and the Quezon National Forest Park.
  • B. Quirino
    Quirino is a landlocked province in the Cagayan Valley region of the Philippines known for its mountainous terrain, caves, and eco-tourism attractions.
  • C. Tarlac
    Tarlac is a landlocked province in the Central Luzon region of the Philippines known for its culturally diverse population and agricultural economy.
  • D. Quezon, Nueva Ecija
    Quezon, Nueva Ecija is a landlocked agricultural municipality in the Philippines known for its rice farming and rural communities within the province of Nueva Ecija.
  • E. Nueva Ecija
    Nueva Ecija is a landlocked agricultural province in Central Luzon, Philippines, known as a major rice-producing area and home to diverse ethnolinguistic groups.
  • 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_69b3453d91548190b4d4ef8fe52aa2ac completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e891bc08190831187da4f553f48 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a872fd6881908a3fbe37e7c35c92 completed March 14, 2026, 6:26 p.m.
Created at: March 12, 2026, 11:05 p.m.