Triple

T35438247
Position Surface form Disambiguated ID Type / Status
Subject National Airports Corporation of Papua New Guinea E1024268 entity
Predicate operatesAirport P38515 FINISHED
Object Aropa Airport
Aropa Airport is a regional airport on Bougainville Island in Papua New Guinea that serves as an important gateway for domestic air travel to the area.
E2143448 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: Aropa Airport | Statement: [National Airports Corporation of Papua New Guinea, operatesAirport, Aropa Airport]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Aropa Airport
Triple: [National Airports Corporation of Papua New Guinea, operatesAirport, Aropa Airport]
Generated description
Aropa Airport is a regional airport on Bougainville Island in Papua New Guinea that serves as an important gateway for domestic air travel to the area.

Provenance (5 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_69f76df743c48190aecb6dd79efb0d95 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f795bf884481908cfa2e923eaa2864 completed May 3, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a221e808190883e64979c627a22 completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384af0370c8190b49b96626cfb98c2 completed June 21, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_6a384b839a308190a63708ae678946da completed June 21, 2026, 8:37 p.m.
Created at: May 3, 2026, 4:04 p.m.