Triple
T35190972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slacker |
E1016117
|
entity |
| Predicate | hasNoConventionalProtagonist |
P204297
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Slacker, hasNoConventionalProtagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoConventionalProtagonist Context triple: [Slacker, hasNoConventionalProtagonist, true]
-
A.
hasNoHumanProtagonist
Indicates that in the described work or narrative, none of the main protagonists are human characters.
-
B.
hasOrphanProtagonist
Indicates that the main character in a work is an orphan, lacking one or both parents as part of the story’s premise.
-
C.
doesNotFeatureCharacterDirectly
Indicates that the subject work does not include the specified character as an on-screen, on-page, or otherwise directly appearing participant in its content.
-
D.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
E.
hasNoFrameNarrative
Indicates that a narrative work lacks an overarching frame story or framing device that encloses or contextualizes its main narrative.
- F. None of above. chosen
Provenance (4 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_69f76ddd815c8190b822eea06630f9fb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a036f0569cc8190a8ac7f4e07145d15 |
completed | May 12, 2026, 6:18 p.m. |
| PD | Predicate disambiguation | batch_6a036c42cf2481908760c7d48b9fc001 |
completed | May 12, 2026, 6:06 p.m. |
| PDg | Predicate description generation | batch_6a036f04c07c819099520ec48ee81461 |
completed | May 12, 2026, 6:18 p.m. |
Created at: May 3, 2026, 4:02 p.m.