Triple

T25745964
Position Surface form Disambiguated ID Type / Status
Subject Lincoln LS E648344 entity
Predicate notableAward P11 FINISHED
Object Motor Trend Car of the Year 2000
Motor Trend Car of the Year 2000 is an annual automotive award recognizing the most outstanding new car model introduced for the 2000 model year, which was won by the Lincoln LS.
E1693561 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: Motor Trend Car of the Year 2000 | Statement: [Lincoln LS, notableAward, Motor Trend Car of the Year 2000]
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: Motor Trend Car of the Year 2000
Triple: [Lincoln LS, notableAward, Motor Trend Car of the Year 2000]
Generated description
Motor Trend Car of the Year 2000 is an annual automotive award recognizing the most outstanding new car model introduced for the 2000 model year, which was won by the Lincoln LS.

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_69e7ab306eec8190b05c312c6ab186b8 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fd1e9dd081908c70074c8aa49e51 completed May 2, 2026, 1:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cc0989c08190b9a0b48d2c0184f9 completed May 22, 2026, 9:35 p.m.
NEDg Description generation batch_6a10cc9f320c8190b958be1f0075cd8f completed May 22, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_6a10cdf9537481909131c59b126e69b6 completed May 22, 2026, 9:43 p.m.
Created at: April 22, 2026, 3:51 a.m.