Triple

T26695433
Position Surface form Disambiguated ID Type / Status
Subject Bill Tilman E673004 entity
Predicate notableWork P4 FINISHED
Object Two Mountains and a River
Two Mountains and a River is a classic mountaineering and travel memoir by British explorer Bill Tilman, recounting his adventurous expeditions in the Himalayas and Central Asia.
E1736973 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: Two Mountains and a River | Statement: [Bill Tilman, notableWork, Two Mountains and a River]
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: Two Mountains and a River
Triple: [Bill Tilman, notableWork, Two Mountains and a River]
Generated description
Two Mountains and a River is a classic mountaineering and travel memoir by British explorer Bill Tilman, recounting his adventurous expeditions in the Himalayas and Central Asia.

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_69eecda2066c8190a344218afa5e89c1 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6177b7a04819084c7380ff22e0379 completed May 2, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe7e8b5c819084088f71eb72608f completed May 23, 2026, 7:22 p.m.
NEDg Description generation batch_6a11ff162d588190a1f98429d7fe5154 completed May 23, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_6a11ff99fdbc81909fd5646fb32987a2 completed May 23, 2026, 7:27 p.m.
Created at: April 27, 2026, 3:28 a.m.