Triple

T30161387
Position Surface form Disambiguated ID Type / Status
Subject London Underground Circle line E766674 entity
Predicate depot P14646 FINISHED
Object Triangle Sidings
Triangle Sidings is a London Underground train stabling and maintenance facility serving the Circle line.
E1900512 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: Triangle Sidings | Statement: [London Underground Circle line, depot, Triangle Sidings]
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: Triangle Sidings
Triple: [London Underground Circle line, depot, Triangle Sidings]
Generated description
Triangle Sidings is a London Underground train stabling and maintenance facility serving the Circle line.

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_69f2247a968881909d79c18f2bfcb275 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67edb30d8819097a9f90443428fc2 completed May 2, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274cc73eb481909555e2886d37751d completed June 8, 2026, 11:14 p.m.
NEDg Description generation batch_6a274d5a67ec81909f2e7f0b7a91a280 completed June 8, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_6a274dbbc3e481909601c15e6843fe92 completed June 8, 2026, 11:18 p.m.
Created at: April 29, 2026, 7:21 p.m.