Triple

T28990652
Position Surface form Disambiguated ID Type / Status
Subject Banbury Cross junction E736016 entity
Predicate hasNearbyStreet P8235 FINISHED
Object South Bar Street
South Bar Street is a main road in Banbury, Oxfordshire, forming part of the historic town center’s street network.
 E2287442 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: South Bar Street | Statement: [Banbury Cross junction, hasNearbyStreet, South Bar Street]
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: South Bar Street
Triple: [Banbury Cross junction, hasNearbyStreet, South Bar Street]
Generated description
South Bar Street is a main road in Banbury, Oxfordshire, forming part of the historic town center’s street network.

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_69f077eacd0481908ef0bafd74491cd0 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f65f7d3b5c8190937aaddff2879989 completed May 2, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a478f0295bc8190b3dcf01c10cf5f93 completed July 3, 2026, 10:29 a.m.
NEDg Description generation batch_6a479055e2d88190a60a10f0a7801ec2 completed July 3, 2026, 10:35 a.m.
NED2 Entity disambiguation (via description) batch_6a59ee2822448190862b2d0204b724ba completed July 17, 2026, 8:56 a.m.
Created at: April 28, 2026, 9:24 a.m.