Triple

T25819293
Position Surface form Disambiguated ID Type / Status
Subject Continental Mark III E650353 entity
Predicate designer P184 FINISHED
Object Lee Iacocca (program champion)
Lee Iacocca (program champion) was a prominent American automotive executive best known for leading major product programs at Ford and Chrysler, including influential luxury and performance vehicles.
E1696578 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: Lee Iacocca (program champion) | Statement: [Continental Mark III, designer, Lee Iacocca (program champion)]
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: Lee Iacocca (program champion)
Triple: [Continental Mark III, designer, Lee Iacocca (program champion)]
Generated description
Lee Iacocca (program champion) was a prominent American automotive executive best known for leading major product programs at Ford and Chrysler, including influential luxury and performance vehicles.

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_69e7ab367fcc8190a5ff1e7f3da046a4 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6018f91248190985323d1a678e539 completed May 2, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da221cdc81908c3604db75790900 completed May 22, 2026, 10:35 p.m.
NEDg Description generation batch_6a10dc54e00c8190b6e45779b281bc2a completed May 22, 2026, 10:44 p.m.
NED2 Entity disambiguation (via description) batch_6a10dcaf4bd48190b5ed702e33b40441 completed May 22, 2026, 10:46 p.m.
Created at: April 22, 2026, 7:28 a.m.