Triple

T27310641
Position Surface form Disambiguated ID Type / Status
Subject Passerina ciris E689192 entity
Predicate commonName P570 FINISHED
Object painted bunting
The painted bunting is a small North American songbird renowned for the male’s vivid rainbow-like plumage and secretive behavior in dense thickets.
E1768818 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: painted bunting | Statement: [Passerina ciris, commonName, painted bunting]
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: painted bunting
Triple: [Passerina ciris, commonName, painted bunting]
Generated description
The painted bunting is a small North American songbird renowned for the male’s vivid rainbow-like plumage and secretive behavior in dense thickets.

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_69ef355b931c8190a63cafaf7bcc008b completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627b24dd48190a6192153354240ca completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7cc8e388190be35d2469f5de894 completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a836c29081909204e8050475b90a completed May 24, 2026, 7:26 a.m.
NED2 Entity disambiguation (via description) batch_6a12a8c42ba88190bff494510a3bbbcd completed May 24, 2026, 7:29 a.m.
Created at: April 27, 2026, 11:27 a.m.