Triple

T11145283
Position Surface form Disambiguated ID Type / Status
Subject Cebu Pacific E263652 entity
Predicate subsidiary P258 FINISHED
Object Cebgo E597153 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: Cebgo | Statement: [Cebu Pacific, subsidiary, Cebgo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cebgo
Context triple: [Cebu Pacific, subsidiary, Cebgo]
  • A. Cebgo chosen
    Cebgo is a Philippine low-cost regional airline operating domestic routes and serving as a feeder carrier for Cebu Pacific.
  • B. Cembo
    Cembo is a residential and commercial barangay in Makati City, Philippines, known for its dense urban community and proximity to major business districts.
  • C. Gongnie
    Gongnie was the personal name of King You of Zhou, the last king of the Western Zhou dynasty in ancient China.
  • D. Tebuange
    Tebuange is a small village settlement located on the island of Nonouti in Kiribati, likely characterized by a traditional Pacific island community and subsistence lifestyle.
  • E. Gooigi
    Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8634d5481909b114d30a542ea3f completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4421d35f48190a5905fbab39f4015 completed April 19, 2026, 2:46 a.m.
Created at: April 8, 2026, 9:28 p.m.