Triple
T36647817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veere Di Wedding |
E904758
|
entity |
| Predicate | leadCharacterCount |
P32078
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Veere Di Wedding, leadCharacterCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterCount Context triple: [Veere Di Wedding, leadCharacterCount, 4]
-
A.
numberOfCharacters
chosen
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
B.
graphicCharactersCount
Indicates the number of printable (non-control) characters present in a given text or string.
-
C.
leadCharacterField
Indicates that one entity serves as the primary or main character associated with another entity, such as a work or production.
-
D.
leadCharacterBasedOn
Indicates that a lead character is derived from, inspired by, or adapted from a particular source entity (such as a real person, another character, or existing work).
-
E.
leadCharacterStatus
Indicates the role or condition of an entity when it serves as the primary or central character in a narrative 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_69f76e6d3a3c81909db73eda9e0516bd |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.