Triple
T14902088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murderer, Hope of Women |
E360030
|
entity |
| Predicate | hasDramatisPersonae |
P25662
|
FINISHED |
| Object | male protagonist |
—
|
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: male protagonist | Statement: [Murderer, Hope of Women, hasDramatisPersonae, male protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDramatisPersonae Context triple: [Murderer, Hope of Women, hasDramatisPersonae, male protagonist]
-
A.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
B.
hasCrewMember
Indicates that an entity includes or employs another entity as a member of its crew.
-
C.
hasFictionalStaffMember
Indicates that an entity includes or employs a staff member who is a fictional character.
-
D.
originalCast
Indicates that the subject is a member of the initial group of performers or participants who first originated a role or production.
-
E.
hasFictionalRole
chosen
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded60b24008190bd272c0d61329400 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:11 a.m.