Triple

T28888141
Position Surface form Disambiguated ID Type / Status
Subject Calandrella E732621 entity
Predicate includesTaxon P1393 FINISHED
Object Calandrella yunnanensis
Calandrella yunnanensis is a species of lark in the genus Calandrella, a group of small passerine birds found in open habitats of Eurasia and Africa.
E1837927 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: Calandrella yunnanensis | Statement: [Calandrella, includesTaxon, Calandrella yunnanensis]
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: Calandrella yunnanensis
Triple: [Calandrella, includesTaxon, Calandrella yunnanensis]
Generated description
Calandrella yunnanensis is a species of lark in the genus Calandrella, a group of small passerine birds found in open habitats of Eurasia and Africa.

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_69f05b07bdec819080cadfe147aa1f25 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65a7386a081908edc6be9122159f8 completed May 2, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec30d5308190893a55fde48338f1 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f1eb88d48190bf846d2e427ecd6e completed June 7, 2026, 4:22 a.m.
NED2 Entity disambiguation (via description) batch_6a24f24d6a088190a691f54096fe3ca7 completed June 7, 2026, 4:23 a.m.
Created at: April 28, 2026, 7:52 a.m.