Triple

T35166164
Position Surface form Disambiguated ID Type / Status
Subject Corporation Street, Birmingham E1015408 entity
Predicate hasPublicTransportConnection P3791 FINISHED
Object Corporation Street tram stop
Corporation Street tram stop is a Midland Metro light rail stop in Birmingham city centre serving passengers on the West Midlands Metro network.
 E2127420 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: Corporation Street tram stop | Statement: [Corporation Street, Birmingham, hasPublicTransportConnection, Corporation Street tram stop]
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: Corporation Street tram stop
Triple: [Corporation Street, Birmingham, hasPublicTransportConnection, Corporation Street tram stop]
Generated description
Corporation Street tram stop is a Midland Metro light rail stop in Birmingham city centre serving passengers on the West Midlands Metro 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_69f76ddbfde081908bffc91572368289 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78d34109c8190acd2299e5f73fd1a completed May 3, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d96f73848190a28182590c056499 completed June 21, 2026, 12:30 p.m.
NEDg Description generation batch_6a37dbce092c81908ded9e525a778907 completed June 21, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_6a37dc0c0a5081908ce1002b7181b433 completed June 21, 2026, 12:41 p.m.
Created at: May 3, 2026, 4:02 p.m.