Triple

T7865749
Position Surface form Disambiguated ID Type / Status
Subject Aklanon language E182609 entity
Predicate spokenIn P2266 FINISHED
Object Antique, Philippines E675069 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: Antique, Philippines | Statement: [Aklanon language, spokenIn, Antique, Philippines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antique, Philippines
Context triple: [Aklanon language, spokenIn, Antique, Philippines]
  • A. Antique, Philippines chosen
    Antique is a province in the Western Visayas region of the Philippines known for its mountainous landscapes, coastal communities, and rich Kinaray-a cultural heritage.
  • B. Philippine
    Philippine is a feminine given name of French origin historically borne by European nobility and royalty.
  • C. PHILIPPINE
    PHILIPPINE is the radio callsign used by Philippine Airlines for its flight operations and air traffic communications.
  • D. Ermita, Manila
    Ermita, Manila is a historic district in the city of Manila known as a major center for government institutions, education, healthcare, and tourism.
  • E. Tondo, Manila, Philippines
    Tondo, Manila, Philippines is a densely populated and historically significant district of Manila known for its working-class communities and vibrant urban culture.
  • 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_69ca82894d9081908a832bfce71a4714 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3844eacc81908f8e1e5fc4dafec8 completed March 31, 2026, 2:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b5908a88190bc00f0d6dbde0b58 completed March 31, 2026, 5:27 a.m.
Created at: March 30, 2026, 4:54 p.m.