Triple

T27873696
Position Surface form Disambiguated ID Type / Status
Subject GE U-series locomotives E704867 entity
Predicate notableModel P1503 FINISHED
Object GE U26C
The GE U26C is a six-axle diesel-electric locomotive built by General Electric primarily for heavy freight service in international markets such as Brazil, South Africa, and New Zealand.
 E1799265 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: GE U26C | Statement: [GE U-series locomotives, notableModel, GE U26C]
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: GE U26C
Triple: [GE U-series locomotives, notableModel, GE U26C]
Generated description
The GE U26C is a six-axle diesel-electric locomotive built by General Electric primarily for heavy freight service in international markets such as Brazil, South Africa, and New Zealand.

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_69ef84111bb4819084298f994b31c62f completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6397dce7c819095d1b64ae7c0fef8 completed May 2, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b87f36608190ae9143b0e6b73cad completed May 26, 2026, 3:13 p.m.
NEDg Description generation batch_6a15bb1f07c48190aaecc330abbba12f completed May 26, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_6a15bbab614c81908b86ec6c4043e1d0 completed May 26, 2026, 3:26 p.m.
Created at: April 27, 2026, 6:26 p.m.