Triple

T27687630
Position Surface form Disambiguated ID Type / Status
Subject Wolseley E698073 entity
Predicate finalModelsBasedOn P88131 FINISHED
Object Austin 1800
The Austin 1800 is a mid-sized British family car produced by BMC in the 1960s and 1970s, known for its spacious interior, advanced Hydrolastic suspension, and distinctive “Landcrab” styling.
E1784491 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: Austin 1800 | Statement: [Wolseley, finalModelsBasedOn, Austin 1800]
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: Austin 1800
Triple: [Wolseley, finalModelsBasedOn, Austin 1800]
Generated description
The Austin 1800 is a mid-sized British family car produced by BMC in the 1960s and 1970s, known for its spacious interior, advanced Hydrolastic suspension, and distinctive “Landcrab” styling.

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_69ef590df8708190af5488f0638e790c completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f74d41bf048190895bc0591447d045 completed May 3, 2026, 1:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12dab19e148190a7265456accbb535 completed May 24, 2026, 11:02 a.m.
NEDg Description generation batch_6a12dcb81e7c8190aff8806c7d06e8d7 completed May 24, 2026, 11:10 a.m.
NED2 Entity disambiguation (via description) batch_6a12dd3ba39481909149d5d9eb7dd5eb completed May 24, 2026, 11:12 a.m.
Created at: April 27, 2026, 2:50 p.m.