Triple

T25102511
Position Surface form Disambiguated ID Type / Status
Subject South Papua Province E628767 entity
Predicate hasTransportHub P2413 FINISHED
Object Mopah Airport in Merauke
Mopah Airport in Merauke is a regional airport serving the city of Merauke and surrounding areas in Indonesia’s South Papua region, providing vital air connectivity for passengers and cargo.
E1663789 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: Mopah Airport in Merauke | Statement: [South Papua Province, hasTransportHub, Mopah Airport in Merauke]
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: Mopah Airport in Merauke
Triple: [South Papua Province, hasTransportHub, Mopah Airport in Merauke]
Generated description
Mopah Airport in Merauke is a regional airport serving the city of Merauke and surrounding areas in Indonesia’s South Papua region, providing vital air connectivity for passengers and cargo.

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_69e2ff3071548190b62d1ac237397197 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f464be45448190b42c7d880d8550c8 completed May 1, 2026, 8:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048f02a308190adf7e34caf827666 completed May 22, 2026, 12:15 p.m.
NEDg Description generation batch_6a104a6df4208190b8fa9647b516b7fc completed May 22, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a104c29b7ec8190b6ecf8d745b9ce90 completed May 22, 2026, 12:29 p.m.
Created at: April 18, 2026, 6:26 a.m.