Triple

T2329565
Position Surface form Disambiguated ID Type / Status
Subject Soccsksargen E48369 entity
Predicate namedAfter P63 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: [Soccsksargen, namedAfter, Sarangani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarangani
Context triple: [Soccsksargen, namedAfter, 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. Surigaonon
    Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
  • D. Talokan
    Talokan is a fictional underwater Mesoamerican-inspired kingdom ruled by Namor in the Marvel Cinematic Universe film "Black Panther: Wakanda Forever."
  • E. Dauin
    Dauin is a coastal municipality in Negros Oriental, Philippines, known for its rich marine biodiversity and popular dive sites, including access to the renowned Apo Island.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc667235c819086140af9db961203 completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8786d508190aac531a88fc5076f completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:50 p.m.