Triple

T5344276
Position Surface form Disambiguated ID Type / Status
Subject Kinder Low E124014 entity
Predicate access P1017 FINISHED
Object public right of way LITERAL FINISHED

How this triple was built (1 step)

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: public right of way | Statement: [Kinder Low, access, public right of way]

Provenance (2 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_69bd464be27081908807b40b75c1bbae completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85ea5e748190a9943de794e5c1ec completed March 20, 2026, 5:37 p.m.
Created at: March 20, 2026, 2:01 p.m.