Triple

T10798294
Position Surface form Disambiguated ID Type / Status
Subject Imus River E254767 entity
Predicate region P40 FINISHED
Object Calabarzon E97442 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: Calabarzon | Statement: [Imus River, region, Calabarzon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calabarzon
Context triple: [Imus River, region, Calabarzon]
  • A. Calabarzon chosen
    Calabarzon is a populous and industrialized region in the southern part of Luzon in the Philippines, known for its mix of urban centers, agricultural areas, and manufacturing hubs.
  • B. Aguiguan
    Aguiguan is a small, uninhabited island in the Northern Mariana Islands known for its rugged terrain and seabird colonies.
  • C. Ibanag
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • D. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • E. Gumaca
    Gumaca is a coastal municipality in the province of Quezon in the Philippines, known for its historic churches and role as a local commercial center.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73334feb08190aae967eaa37659f7 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69de84f1fdfc8190a31a13ae434e56c1 completed April 14, 2026, 6:18 p.m.
Created at: April 8, 2026, 9:17 p.m.