Triple

T23942742
Position Surface form Disambiguated ID Type / Status
Subject Tukang Besi Islands E602827 entity
Predicate alsoKnownAs P39 FINISHED
Object Kepulauan Tukang Besi
Kepulauan Tukang Besi is an island group in Southeast Sulawesi, Indonesia, renowned for its rich marine biodiversity and popular dive sites within the Wakatobi National Park.
E1622408 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: Kepulauan Tukang Besi | Statement: [Tukang Besi Islands, alsoKnownAs, Kepulauan Tukang Besi]
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: Kepulauan Tukang Besi
Triple: [Tukang Besi Islands, alsoKnownAs, Kepulauan Tukang Besi]
Generated description
Kepulauan Tukang Besi is an island group in Southeast Sulawesi, Indonesia, renowned for its rich marine biodiversity and popular dive sites within the Wakatobi National Park.

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_69e2953e4924819093f1c24c03476b42 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d02bf38081909c99b98e04a8d2aa completed April 29, 2026, 9:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0facf7ec0881909d8f0fc4d71a4b36 completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fae6318c8819099bf0565a01b5312 completed May 22, 2026, 1:16 a.m.
NED2 Entity disambiguation (via description) batch_6a0faefcb9048190abf1ccd608f1b607 completed May 22, 2026, 1:18 a.m.
Created at: April 17, 2026, 9:10 p.m.