Triple

T4676769
Position Surface form Disambiguated ID Type / Status
Subject Miguel Malvar E103699 entity
Predicate residence P75 FINISHED
Object Batangas E188572 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: Batangas | Statement: [Miguel Malvar, residence, Batangas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batangas
Context triple: [Miguel Malvar, residence, Batangas]
  • A. Batangas chosen
    Batangas is a province in the Calabarzon region of the Philippines known for its beaches, diving spots, and the Taal Volcano.
  • B. Camarines Sur
    Camarines Sur is a province in the Bicol Region of the Philippines known for its rich Bikolano culture, religious heritage sites, and natural attractions such as lakes, mountains, and eco-tourism destinations.
  • C. Pampanga
    Pampanga is a province in the Central Luzon region of the Philippines, known for its rich culinary heritage, vibrant festivals, and significant role in the country’s history and culture.
  • D. Zambales
    Zambales is a coastal province in the Central Luzon region of the Philippines, known for its beaches, mangoes, and ethnolinguistic diversity.
  • E. Batangas City
    Batangas City is a major port and industrial hub in the province of Batangas in the Philippines, known for its oil refineries, commercial activity, and role as a gateway to nearby islands.
  • 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63685cb88190ac1904e2c7eb6b61 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfb6fb95008190af52d015903bca5c completed March 22, 2026, 9:31 a.m.
Created at: March 20, 2026, 1:16 p.m.