Triple

T11741205
Position Surface form Disambiguated ID Type / Status
Subject Dumalag E279156 entity
Predicate hasNearbyMunicipality P4647 FINISHED
Object Maayon E279160 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: Maayon | Statement: [Dumalag, hasNearbyMunicipality, Maayon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maayon
Context triple: [Dumalag, hasNearbyMunicipality, Maayon]
  • A. Maayon chosen
    Maayon is a rural municipality in the province of Capiz in the Philippines, known for its agricultural landscape and small-town community.
  • B. Mayoon
    Mayoon is a village in the Lower Hunza region of Gilgit-Baltistan, Pakistan, known for its mountainous landscape and traditional Hunza culture.
  • C. Magayon
    Magayon is a legendary maiden from Bicolano folklore whose tragic love story is said to have inspired the name and mythic origins of Mayon Volcano in the Philippines.
  • D. Maay Maay
    Maay Maay is a Cushitic language spoken primarily by the Maay-speaking Somali communities in southern Somalia and neighboring regions.
  • E. Maay
    Maay is a major dialect of the Somali language spoken primarily by the Rahanweyn (Digil-Mirifle) communities in southern Somalia.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f025f88190a39280806c9d7c33 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019d331888190866bdd04f6c73e08 completed April 28, 2026, 2:22 a.m.
Created at: April 8, 2026, 9:41 p.m.