Triple

T3354666
Position Surface form Disambiguated ID Type / Status
Subject Bikolano people E70576 entity
Predicate traditionalDish P19483 FINISHED
Object Pinangat E338025 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: Pinangat | Statement: [Bikolano people, traditionalDish, Pinangat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinangat
Context triple: [Bikolano people, traditionalDish, Pinangat]
  • A. Pinangat chosen
    Pinangat is a traditional Filipino dish from the Bicol Region made of taro leaves, coconut milk, and chilies, known for its rich, spicy flavor.
  • B. Punakapina
    Punakapina is the Finnish Civil War of 1918, a conflict between the socialist Reds and conservative Whites that shaped Finland’s early independence.
  • C. Calabarzon
    Calabarzon is a populous and industrialized region in the southern part of Luzon in the Philippines, known for its mix of urban centers, agricultural areas, and manufacturing hubs.
  • D. Pototan
    Pototan is a first-class municipality in the Philippine province of Iloilo, known for its agricultural economy and its popular Christmas lights festival.
  • E. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • 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_69ad85a4ef7c8190a29e2bbd6fa454e4 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb24036848190bac779d17dfdce3b completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b325373a1c8190b26d883e2f0dd92b completed March 12, 2026, 8:42 p.m.
Created at: March 8, 2026, 3:13 p.m.