Triple

T2402044
Position Surface form Disambiguated ID Type / Status
Subject Intramuros E47789 entity
Predicate nearbyDistrict P18717 FINISHED
Object Binondo E49336 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: Binondo | Statement: [Intramuros, nearbyDistrict, Binondo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Binondo
Context triple: [Intramuros, nearbyDistrict, Binondo]
  • A. Binondo chosen
    Binondo is Manila’s historic Chinatown, renowned as one of the oldest Chinatowns in the world and a bustling center of commerce, culture, and Chinese-Filipino heritage.
  • B. Ibanag
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • C. Malpaso
    Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
  • D. Dasmariñas
    Dasmariñas is a rapidly urbanizing city in the province of Cavite in the Philippines, known as a major residential, commercial, and educational hub south of Metro Manila.
  • E. Surigaonon
    Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
  • 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc8f623908190875fdbc95c944f33 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3e554c08190b5268c41ab34f4d9 completed March 9, 2026, 11:49 a.m.
Created at: March 4, 2026, 7:57 p.m.