Triple

T34360169
Position Surface form Disambiguated ID Type / Status
Subject Tadyawan E881850 entity
Predicate hasAlternateName P39 FINISHED
Object Tadiwan
Tadiwan is an alternate name for the Tadyawan, an indigenous group in the Philippines known for their distinct culture and language.
E2093662 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: Tadiwan | Statement: [Tadyawan, hasAlternateName, Tadiwan]
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: Tadiwan
Triple: [Tadyawan, hasAlternateName, Tadiwan]
Generated description
Tadiwan is an alternate name for the Tadyawan, an indigenous group in the Philippines known for their distinct culture and language.

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_69f349be5c9c81908dc726ae1f4c68f2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71829be048190a5ddf679f09aa7c3 completed May 3, 2026, 9:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3704a597548190a01489ead3a1ec86 completed June 20, 2026, 9:22 p.m.
NEDg Description generation batch_6a370543b0c08190a81fe42444b9fbe6 completed June 20, 2026, 9:25 p.m.
NED2 Entity disambiguation (via description) batch_6a3705f992b4819080ee9743fab5932d completed June 20, 2026, 9:28 p.m.
Created at: May 1, 2026, 1:58 a.m.