Triple

T24084349
Position Surface form Disambiguated ID Type / Status
Subject Kallahan E596592 entity
Predicate hasDialect P4251 FINISHED
Object Western Kalanguya
Western Kalanguya is a dialect of the Kallahan language spoken by the Kalanguya people in the northern Philippines.
 E1628354 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: Western Kalanguya | Statement: [Kallahan, hasDialect, Western Kalanguya]
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: Western Kalanguya
Triple: [Kallahan, hasDialect, Western Kalanguya]
Generated description
Western Kalanguya is a dialect of the Kallahan language spoken by the Kalanguya people in the northern Philippines.

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_69e288c4638c81909bacc28a1e3d436b completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dc279ac48190b60a0753981f0b97 completed April 29, 2026, 10:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc99e4d988190972cf47c9e3e2da1 completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcb0d718c81909c02cea23a2bffdc completed May 22, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcbe802788190b1383ce61a5e0cc4 completed May 22, 2026, 3:22 a.m.
Created at: April 17, 2026, 10:44 p.m.