Triple
T6371808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Start TV |
E143364
|
entity |
| Predicate | focusCharacterType |
P49696
|
FINISHED |
| Object | female protagonists |
—
|
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: female protagonists | Statement: [Start TV, focusCharacterType, female protagonists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusCharacterType Context triple: [Start TV, focusCharacterType, female protagonists]
-
A.
characterizationFocus
Indicates that the primary emphasis or concern of a characterization is directed toward a particular aspect, feature, or dimension of the subject.
-
B.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
C.
workCharacterType
chosen
Indicates that a work involves or features a character of a specified type or role.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
- 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c068289eac8190a17affed87340c1f |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.