Triple

T30625600
Position Surface form Disambiguated ID Type / Status
Subject Oribi Gorge E779566 entity
Predicate hasFauna P950 FINISHED
Object samango monkey
The samango monkey is an arboreal Old World monkey native to the forests of eastern and southern Africa, known for its distinctive dark fur, white throat, and reliance on high-canopy habitats.
E1923161 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: samango monkey | Statement: [Oribi Gorge, hasFauna, samango monkey]
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: samango monkey
Triple: [Oribi Gorge, hasFauna, samango monkey]
Generated description
The samango monkey is an arboreal Old World monkey native to the forests of eastern and southern Africa, known for its distinctive dark fur, white throat, and reliance on high-canopy habitats.

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_69f224a431548190a44ad9d088dbf91f completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68a1a08208190be3da494890e15a9 completed May 2, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2863e7d48c81909ba55aaba4e47bc6 completed June 9, 2026, 7:05 p.m.
NEDg Description generation batch_6a2864de7ca081909869bd52d86a739a completed June 9, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_6a2865f827a48190848331baed146005 completed June 9, 2026, 7:14 p.m.
Created at: April 29, 2026, 8:27 p.m.