Triple

T3112770
Position Surface form Disambiguated ID Type / Status
Subject Lineyte-Samarnon E64987 entity
Predicate spokenInProvince P44118 FINISHED
Object Biliran E261520 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: Biliran | Statement: [Lineyte-Samarnon, spokenInProvince, Biliran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biliran
Context triple: [Lineyte-Samarnon, spokenInProvince, Biliran]
  • A. Biliran chosen
    Biliran is an island province in the central Philippines known for its volcanic landscapes, waterfalls, and coastal scenery.
  • B. Sibulan
    Sibulan is a coastal municipality in the Philippine province of Negros Oriental known as a gateway to Dumaguete City and for its local airport and seaport.
  • C. Bislig
    Bislig is a coastal city in the Caraga region of Mindanao in the Philippines, known for its proximity to the Tinuy-an Falls and its history as a former major paper-mill town.
  • D. Balanga
    Balanga is a coastal city in the province of Bataan in the Philippines, situated along the shores of Manila Bay.
  • E. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43c79448190aa72f707319e8c5e completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f5cfc7c8190b867794c0e9a271e completed March 12, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:04 p.m.