Triple

T21915903
Position Surface form Disambiguated ID Type / Status
Subject Insular Government of the Philippine Islands E541182 entity
Predicate capital P234 FINISHED
Object Manila 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: Manila | Statement: [Insular Government of the Philippine Islands, capital, Manila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manila
Context triple: [Insular Government of the Philippine Islands, capital, Manila]
  • A. Manila
    Manila is the OpenStack shared file system service that provides scalable, API-driven management of networked file shares.
  • B. Manila chosen
    Manila is the capital city of the Philippines, a historic and densely populated coastal metropolis that has long served as the country’s political, economic, and cultural center.
  • C. Manila
    Manila is a web-based content management and blogging system developed by UserLand Software that was popular in the early days of personal publishing on the internet.
  • D. Manila
    Manila is a fictional member of the Professor's heist crew in the Spanish television series "Money Heist" ("La Casa de Papel").
  • E. Quezon City, Philippines
    Quezon City, Philippines is a highly urbanized city in Metro Manila that serves as a major political, educational, and commercial center of the country.
  • 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_69e0c47c4b9c8190a5586a75f5f36453 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f123378140819090a30453c1db7f38 completed April 28, 2026, 9:14 p.m.
Created at: April 16, 2026, 7:43 p.m.