Triple

T30013129
Position Surface form Disambiguated ID Type / Status
Subject Harrod–Domar growth model E762520 entity
Predicate namedAfter P63 FINISHED
Object Roy F. Harrod
Roy F. Harrod was a British economist known for his pioneering work in macroeconomic growth theory and his collaboration with and biography of John Maynard Keynes.
 E2293420 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: Roy F. Harrod | Statement: [Harrod–Domar growth model, namedAfter, Roy F. Harrod]
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: Roy F. Harrod
Triple: [Harrod–Domar growth model, namedAfter, Roy F. Harrod]
Generated description
Roy F. Harrod was a British economist known for his pioneering work in macroeconomic growth theory and his collaboration with and biography of John Maynard Keynes.

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_69f2246b0c84819094f1250b6a02d277 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6798294288190ae5a5e0a83a20044 completed May 2, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7aa615fa088190bae6438177964f09 completed Aug. 11, 2026, 4:33 a.m.
NEDg Description generation batch_6a7aa766e10081908c3309ebf51fe756 completed Aug. 11, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_6a7aa7bbe43c8190ae6c85c6dd59919a completed Aug. 11, 2026, 4:40 a.m.
Created at: April 29, 2026, 6:44 p.m.