Triple

T30609771
Position Surface form Disambiguated ID Type / Status
Subject Hermosillo Assembly Plant E779143 entity
Predicate productType P87 FINISHED
Object Lincoln vehicles
Lincoln vehicles are a line of luxury automobiles produced by the Lincoln division of Ford Motor Company, known for their premium comfort, upscale features, and refined design.
E1923909 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: Lincoln vehicles | Statement: [Hermosillo Assembly Plant, productType, Lincoln vehicles]
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: Lincoln vehicles
Triple: [Hermosillo Assembly Plant, productType, Lincoln vehicles]
Generated description
Lincoln vehicles are a line of luxury automobiles produced by the Lincoln division of Ford Motor Company, known for their premium comfort, upscale features, and refined design.

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_69f224a21fc08190abd9d8dd9eb6bb4c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f689b87220819084859503a4458c0d completed May 2, 2026, 11:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2863dc2cfc8190a96b0b6e6c5a78e4 completed June 9, 2026, 7:05 p.m.
NEDg Description generation batch_6a28649cba348190b61d110cbbc16abd completed June 9, 2026, 7:08 p.m.
NED2 Entity disambiguation (via description) batch_6a28653331c08190b467fba620124049 completed June 9, 2026, 7:10 p.m.
Created at: April 29, 2026, 8:26 p.m.