Triple

T30000877
Position Surface form Disambiguated ID Type / Status
Subject Mount Chilalo E762162 entity
Predicate ecoregion P948 FINISHED
Object Ethiopian montane forests
The Ethiopian montane forests are a high-altitude ecoregion characterized by moist, biodiverse Afromontane woodlands and cloud forests found on Ethiopia’s mountains and high plateaus.
 E1894500 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: Ethiopian montane forests | Statement: [Mount Chilalo, ecoregion, Ethiopian montane forests]
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: Ethiopian montane forests
Triple: [Mount Chilalo, ecoregion, Ethiopian montane forests]
Generated description
The Ethiopian montane forests are a high-altitude ecoregion characterized by moist, biodiverse Afromontane woodlands and cloud forests found on Ethiopia’s mountains and high plateaus.

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_69f2246a47ac81909cf5213053687ffc completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6794eecb48190a679439c69a17137 completed May 2, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a272209664481909830cfed0aee69fa completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a272333f384819084456b384bc17a6c completed June 8, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2723e6c6648190801fec9c9fd7f557 completed June 8, 2026, 8:19 p.m.
Created at: April 29, 2026, 6:41 p.m.