Triple

T27860187
Position Surface form Disambiguated ID Type / Status
Subject Family Stand E704204 entity
Predicate locatedIn P40 FINISHED
Object Meadow Lane area
The Meadow Lane area is the surrounding district of Notts County FC’s Meadow Lane stadium in Nottingham, England, encompassing its stands, facilities, and nearby urban environment.
E1790888 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: Meadow Lane area | Statement: [Family Stand, locatedIn, Meadow Lane area]
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: Meadow Lane area
Triple: [Family Stand, locatedIn, Meadow Lane area]
Generated description
The Meadow Lane area is the surrounding district of Notts County FC’s Meadow Lane stadium in Nottingham, England, encompassing its stands, facilities, and nearby urban environment.

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_69ef840e614c8190a88cf9638c14a265 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6394220d88190a9d7d5f5ebcf5e4f completed May 2, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f742e40c819091e7d37ccdf7a47e completed May 24, 2026, 1:04 p.m.
NEDg Description generation batch_6a12f7bb9d188190a07e37281d9d665e completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbaac4c8819080293672dd321aa9 completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 6:17 p.m.