Triple

T32326969
Position Surface form Disambiguated ID Type / Status
Subject Venus on the Half-Shell E825940 entity
Predicate mainCharacter P1183 FINISHED
Object Simon Wagstaff
Simon Wagstaff is the hapless, universe-wandering protagonist of Philip José Farmer’s satirical science fiction novel "Venus on the Half-Shell."
E2001177 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: Simon Wagstaff | Statement: [Venus on the Half-Shell, mainCharacter, Simon Wagstaff]
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: Simon Wagstaff
Triple: [Venus on the Half-Shell, mainCharacter, Simon Wagstaff]
Generated description
Simon Wagstaff is the hapless, universe-wandering protagonist of Philip José Farmer’s satirical science fiction novel "Venus on the Half-Shell."

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_69f34912d0c48190bba75770660320e9 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bde8913c8190b620cc572b19a3ed completed May 3, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a305721e49c8190bd29b0a06694bcb3 completed June 15, 2026, 7:48 p.m.
NEDg Description generation batch_6a3057d0ea1c81908690f5249ffd0f8b completed June 15, 2026, 7:51 p.m.
NED2 Entity disambiguation (via description) batch_6a3058636680819093a2bd6ce0467781 completed June 15, 2026, 7:54 p.m.
Created at: May 1, 2026, 12:47 a.m.