Triple

T21501956
Position Surface form Disambiguated ID Type / Status
Subject Quezon Province E530495 entity
Predicate hasCity P316 FINISHED
Object Tayabas City NE NERFINISHED

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: Tayabas City | Statement: [Quezon Province, hasCity, Tayabas City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tayabas City
Context triple: [Quezon Province, hasCity, Tayabas City]
  • A. Tayabas chosen
    Tayabas is a historic city in the province of Quezon in the Calabarzon region of the Philippines, known for its Spanish-era heritage structures and cultural festivals.
  • B. Calamba City
    Calamba City is a highly urbanized city in the province of Laguna, Philippines, known as the hometown of national hero José Rizal and a major industrial and residential hub south of Metro Manila.
  • C. Tagaytay City
    Tagaytay City is a popular highland tourist destination in the Philippines known for its cool climate and scenic views of Taal Volcano and Taal Lake.
  • D. Las Piñas City
    Las Piñas City is a highly urbanized city in Metro Manila, Philippines, known for its rapid residential and commercial development and its famous Bamboo Organ.
  • E. Pasay City
    Pasay City is a highly urbanized city in Metro Manila, Philippines, known for its major commercial centers, entertainment complexes, and proximity to the Ninoy Aquino International Airport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45bd15481909fba5910765cdda2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea5d209881908754eb07a47e478a completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:24 p.m.