Triple

T2686521
Position Surface form Disambiguated ID Type / Status
Subject South Cotabato E57495 entity
Predicate borderedBy P224 FINISHED
Object Sarangani E257340 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: Sarangani | Statement: [South Cotabato, borderedBy, Sarangani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarangani
Context triple: [South Cotabato, borderedBy, Sarangani]
  • A. Sarangani chosen
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • B. Balanga
    Balanga is a coastal city in the province of Bataan in the Philippines, situated along the shores of Manila Bay.
  • C. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • D. Surigaonon
    Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
  • E. Talokan
    Talokan is a fictional underwater Mesoamerican-inspired kingdom ruled by Namor in the Marvel Cinematic Universe film "Black Panther: Wakanda Forever."
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9ef2fe0819082bbe746ca682a7e completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc63b76e0819084c4d2bd4a9e6d78 completed March 10, 2026, 7:20 a.m.
Created at: March 6, 2026, 9:54 p.m.