Triple

T32586881
Position Surface form Disambiguated ID Type / Status
Subject Scottish railway works network E832944 entity
Predicate hasPart P35 FINISHED
Object Leith railway workshops
Leith railway workshops were a major Scottish railway engineering and maintenance facility located in the port district of Leith, Edinburgh.
E2029424 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: Leith railway workshops | Statement: [Scottish railway works network, hasPart, Leith railway workshops]
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: Leith railway workshops
Triple: [Scottish railway works network, hasPart, Leith railway workshops]
Generated description
Leith railway workshops were a major Scottish railway engineering and maintenance facility located in the port district of Leith, Edinburgh.

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_69f34929ff648190aded9424aa7564ae completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c66f550481909c575eeeed5cd51b completed May 3, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d244d55481908765b718aee0a813 completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d2d1938c8190ae61fa317610c6eb completed June 19, 2026, 5:25 a.m.
NED2 Entity disambiguation (via description) batch_6a34d32fc7148190b2f2839a20b58063 completed June 19, 2026, 5:27 a.m.
Created at: May 1, 2026, 1:04 a.m.