Triple
T18026774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wayne as Tom Doniphon |
E431271
|
entity |
| Predicate | dialogueTrait |
P85534
|
FINISHED |
| Object | plainspoken |
—
|
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: plainspoken | Statement: [John Wayne as Tom Doniphon, dialogueTrait, plainspoken]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogueTrait Context triple: [John Wayne as Tom Doniphon, dialogueTrait, plainspoken]
-
A.
hasDialogueTrait
chosen
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
B.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
C.
dialogue
Indicates that two or more entities are engaged in an exchange of spoken or written communication with each other.
-
D.
dialogueDynamic
Indicates a relationship where entities are engaged in or contributing to an evolving, back-and-forth dialogue or conversational exchange.
-
E.
dialogueDominance
Indicates that one participant exerts greater control or influence over the flow, topics, or outcomes of a dialogue than the other(s).
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c7be308190af0d77c0df6d94ce |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.