Triple
T35812343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Slap |
E1035264
|
entity |
| Predicate | numberOfPointOfViewCharacters |
P115437
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [The Slap, numberOfPointOfViewCharacters, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPointOfViewCharacters Context triple: [The Slap, numberOfPointOfViewCharacters, 8]
-
A.
numberOfPOVCharacters
chosen
Indicates the total count of distinct point-of-view characters associated with a given narrative or work.
-
B.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
C.
numberOfHumanCharacters
Indicates the count of distinct human characters associated with a given entity or context.
-
D.
numberOfAvatarsDescribed
Indicates the count of distinct avatars that are described in a given context or data record.
-
E.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
- 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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.