Triple

T7696016
Position Surface form Disambiguated ID Type / Status
Subject Rizal E174371 entity
Predicate capital P234 FINISHED
Object Antipolo E287754 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: Antipolo | Statement: [Rizal, capital, Antipolo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antipolo
Context triple: [Rizal, capital, Antipolo]
  • A. Antipolo chosen
    Antipolo is a city in the province of Rizal, Philippines, known as a pilgrimage site and suburban residential area east of Metro Manila.
  • B. Muntinlupa
    Muntinlupa is a highly urbanized city in the southern part of Metro Manila in the Philippines, known for housing the New Bilibid Prison and major commercial and residential developments like Alabang.
  • C. Galapagar
    Galapagar is a municipality in the Community of Madrid, Spain, known for its natural surroundings in the Sierra de Guadarrama and its role as a residential town near the capital.
  • D. Olongapo City
    Olongapo City is a highly urbanized coastal city in Zambales, Philippines, known for its proximity to Subic Bay and its history as a former U.S. naval base host community.
  • 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_69c6995966348190939e6c37ba272c06 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70267dab88190ac8e3f643343bf13 completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8acaa6004819088f1ae45ad9b378e completed March 29, 2026, 4:38 a.m.
Created at: March 27, 2026, 4:03 p.m.