Triple

T21468035
Position Surface form Disambiguated ID Type / Status
Subject River Pont E529643 entity
Predicate hasAlternativeName P39 FINISHED
Object Pont River
Pont River is a small river in Northumberland, England, that flows through rural landscapes before joining the River Tyne.
 E1982400 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: Pont River | Statement: [River Pont, hasAlternativeName, Pont 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: Pont River
Triple: [River Pont, hasAlternativeName, Pont River]
Generated description
Pont River is a small river in Northumberland, England, that flows through rural landscapes before joining the River Tyne.

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_69e0c459acb481909bb6ee452a0045c7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9f415d48190a2b0993a4f3c018f completed April 23, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7fb2a27081909d14476e87263821 completed June 14, 2026, 10:17 a.m.
NEDg Description generation batch_6a2e80bfc09c81908b0f21d5dc3629e9 completed June 14, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2e81c63b8081909989e5e18ce19954 completed June 14, 2026, 10:26 a.m.
Created at: April 16, 2026, 6:15 p.m.