Triple
T13990694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Six Million Dollar Man |
E336563
|
entity |
| Predicate | leadCharacterBackground |
P39316
|
FINISHED |
| Object | astronaut |
—
|
LITERAL 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: astronaut | Statement: [The Six Million Dollar Man, leadCharacterBackground, astronaut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterBackground Context triple: [The Six Million Dollar Man, leadCharacterBackground, astronaut]
-
A.
protagonistBackground
Indicates that one entity serves as the background, history, or prior circumstances of the protagonist entity in a narrative or story.
-
B.
hasProtagonistBackground
chosen
Indicates that a work or narrative features a specified background or origin story for its main protagonist.
-
C.
actorBackground
Indicates that one entity provides contextual or biographical background information about an actor entity.
-
D.
leadCharacterStatus
Indicates the role or condition of an entity when it serves as the primary or central character in a narrative or context.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
- F. None of above.
Provenance (3 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb22e388190904fc87765176c91 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.