Triple
T38477579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyranny |
E915586
|
entity |
| Predicate | dialogueImpact |
P191165
|
FINISHED |
| Object | choices affect world state |
—
|
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: choices affect world state | Statement: [Tyranny, dialogueImpact, choices affect world state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogueImpact Context triple: [Tyranny, dialogueImpact, choices affect world state]
-
A.
dialogueDynamic
Indicates a relationship where entities are engaged in or contributing to an evolving, back-and-forth dialogue or conversational exchange.
-
B.
dialogueDominance
Indicates that one participant exerts greater control or influence over the flow, topics, or outcomes of a dialogue than the other(s).
-
C.
dialogue
Indicates that two or more entities are engaged in an exchange of spoken or written communication with each other.
-
D.
dialogueWith
Indicates that two entities are engaged in a mutual conversational exchange or dialogue with each other.
-
E.
dialogueFeature
Indicates that one entity exhibits or involves a particular characteristic, property, or element of a dialogue or conversational exchange with another entity.
- F. None of above. chosen
Provenance (4 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcdaa2bfc08190beccabb0f1782d0d |
completed | May 7, 2026, 6:32 p.m. |
Created at: May 3, 2026, 4:31 p.m.