Triple

T34012920
Position Surface form Disambiguated ID Type / Status
Subject Walk London network E872161 entity
Predicate hasRoute P4374 FINISHED
Object The Wandle Trail
The Wandle Trail is a long-distance walking and cycling route in south London that follows the River Wandle through parks, nature reserves, and historic industrial sites.
E2078122 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: The Wandle Trail | Statement: [Walk London network, hasRoute, The Wandle Trail]
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: The Wandle Trail
Triple: [Walk London network, hasRoute, The Wandle Trail]
Generated description
The Wandle Trail is a long-distance walking and cycling route in south London that follows the River Wandle through parks, nature reserves, and historic industrial sites.

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_69f349a08848819084b348d64c1879c3 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70af0ddd88190a582f37d3b748e97 completed May 3, 2026, 8:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3692efa55c819086fdc7cd7eeb5475 completed June 20, 2026, 1:17 p.m.
NEDg Description generation batch_6a3696cb31e08190baaaca849e172a0e completed June 20, 2026, 1:34 p.m.
NED2 Entity disambiguation (via description) batch_6a369822b9b08190948d96660aa768bb completed June 20, 2026, 1:39 p.m.
Created at: May 1, 2026, 1:51 a.m.