Triple

T11288126
Position Surface form Disambiguated ID Type / Status
Subject Apolinario Mabini E267251 entity
Predicate familyName P18 FINISHED
Object Mabini E710437 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: Mabini | Statement: [Apolinario Mabini, familyName, Mabini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mabini
Context triple: [Apolinario Mabini, familyName, Mabini]
  • A. Mabini chosen
    Mabini is a coastal municipality in the province of Batangas in the Philippines, known for its diving spots and marine biodiversity.
  • B. Makili
    Makili is a small coastal settlement on Atauro Island in East Timor, known for its traditional fishing community and proximity to rich marine biodiversity.
  • C. Bayan
    Bayan is a traditional Sasak village in northern Lombok, Indonesia, known for its preserved indigenous culture, historic mosques, and role as a gateway to the Mount Rinjani area.
  • D. Maragondon
    Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
  • E. Minalin
    Minalin is a municipality in the province of Pampanga in the Philippines, known for its agricultural economy and traditional cultural festivities.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e986b0f08190a414749eaa7f1a5d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f48e190c8190b46d4286e2acaef1 completed April 19, 2026, 3:28 p.m.
Created at: April 8, 2026, 9:32 p.m.