Triple

T14246164
Position Surface form Disambiguated ID Type / Status
Subject Matei Airport E353138 entity
Predicate connectsTo P845 FINISHED
Object Labasa E426418 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: Labasa | Statement: [Matei Airport, connectsTo, Labasa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Labasa
Context triple: [Matei Airport, connectsTo, Labasa]
  • A. Labasa chosen
    Labasa is a major town in northern Fiji on the island of Vanua Levu, known as an important commercial and administrative center for the surrounding sugarcane-growing region.
  • B. Palolo
    Palolo is a residential valley neighborhood in urban Honolulu on the island of Oahu, Hawaii.
  • C. Sarilamak
    Sarilamak is a town in West Sumatra, Indonesia, that serves as the administrative center of Lima Puluh Kota Regency.
  • D. Calabarzon
    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.
  • E. Sarigan
    Sarigan is a small, uninhabited volcanic island in the Northern Mariana Islands known for its active stratovolcano and protected wildlife habitats.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de629464f88190817b190731bab156 completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd282571ec819080d187ecec3ed925 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:08 a.m.