Triple

T25410370
Position Surface form Disambiguated ID Type / Status
Subject River Doethie E636675 entity
Predicate partOf P40 FINISHED
Object Tywi river system
The Tywi river system is a major river network in southwest Wales, known for its scenic valleys, diverse tributaries, and ecological importance.
 E1689716 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: Tywi river system | Statement: [River Doethie, partOf, Tywi river system]
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: Tywi river system
Triple: [River Doethie, partOf, Tywi river system]
Generated description
The Tywi river system is a major river network in southwest Wales, known for its scenic valleys, diverse tributaries, and ecological importance.

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_69e75db361d881908d8701c856da6413 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5b00dfbf08190b20120c052126935 completed May 2, 2026, 8:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c11ffd7c8190a9b8361782a0052f completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c20f4f748190bc19a702f0788086 completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2b5aab88190ab29798dc74baacf completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 1:53 p.m.