Triple

T26708752
Position Surface form Disambiguated ID Type / Status
Subject Pomarea E673350 entity
Predicate hasSpecies P965 FINISHED
Object Pomarea mendozae
Pomarea mendozae is a critically endangered species of monarch flycatcher endemic to the Marquesas Islands in French Polynesia.
E1747224 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: Pomarea mendozae | Statement: [Pomarea, hasSpecies, Pomarea mendozae]
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: Pomarea mendozae
Triple: [Pomarea, hasSpecies, Pomarea mendozae]
Generated description
Pomarea mendozae is a critically endangered species of monarch flycatcher endemic to the Marquesas Islands in French Polynesia.

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_69eecda3a22881908f3061c760b9d542 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f617bcfbb0819092a1334dc7553a97 completed May 2, 2026, 3:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e80a6a081909f70716414d13202 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121f5b854481908b2c1abbbdc7cc89 completed May 23, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a121fd8924881909fe3b5e2eeb1a407 completed May 23, 2026, 9:44 p.m.
Created at: April 27, 2026, 3:35 a.m.