Triple

T23957867
Position Surface form Disambiguated ID Type / Status
Subject Vao E603844 entity
Predicate hasNeighboringLanguage P16383 FINISHED
Object V’ënen Taut
V’ënen Taut is an Oceanic language spoken in Vanuatu, known for its complex phonology and rich system of verbal morphology.
E1609936 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: V’ënen Taut | Statement: [Vao, hasNeighboringLanguage, V’ënen Taut]
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: V’ënen Taut
Triple: [Vao, hasNeighboringLanguage, V’ënen Taut]
Generated description
V’ënen Taut is an Oceanic language spoken in Vanuatu, known for its complex phonology and rich system of verbal morphology.

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_69e2954222288190a7323554d0cca8d7 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d0d85d348190946b578e1a1c3bcc completed April 29, 2026, 9:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f765901208190acf69f6014989670 completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f770a063c81909f356346c9c521ad completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f782b47c08190a221c196ddc9d566 completed May 21, 2026, 9:24 p.m.
Created at: April 17, 2026, 9:22 p.m.