Triple

T28067523
Position Surface form Disambiguated ID Type / Status
Subject Rover P5 E709295 entity
Predicate generation P4860 FINISHED
Object P5 Mark I
P5 Mark I is an early-generation Rover P5 luxury saloon model produced by the British manufacturer Rover in the late 1950s and early 1960s.
 E1799225 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: P5 Mark I | Statement: [Rover P5, generation, P5 Mark I]
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: P5 Mark I
Triple: [Rover P5, generation, P5 Mark I]
Generated description
P5 Mark I is an early-generation Rover P5 luxury saloon model produced by the British manufacturer Rover in the late 1950s and early 1960s.

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_69ef9b6eb6d88190a3fea236eb0f7bed completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6401cee508190a0dd02cb60d72f3b completed May 2, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8cad0b4819080a62b6933717e9f completed May 26, 2026, 3:14 p.m.
NEDg Description generation batch_6a15b930d3a48190b47c9a7921d3f9b5 completed May 26, 2026, 3:16 p.m.
NED2 Entity disambiguation (via description) batch_6a15bb82f47c8190bf0ec0ca187e3c4b completed May 26, 2026, 3:25 p.m.
Created at: April 27, 2026, 8:43 p.m.