Triple
T22021466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilda Dent |
E543854
|
entity |
| Predicate | storyImpact |
P129750
|
FINISHED |
| Object | motivates aspects of Two-Face’s behavior |
—
|
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: motivates aspects of Two-Face’s behavior | Statement: [Gilda Dent, storyImpact, motivates aspects of Two-Face’s behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyImpact Context triple: [Gilda Dent, storyImpact, motivates aspects of Two-Face’s behavior]
-
A.
narrativeImpactOn
chosen
Indicates how one element influences, shapes, or alters the narrative significance or storyline of another.
-
B.
exportImpact
Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
-
C.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
D.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
E.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c7b3308190ac056bef6f82722e |
completed | April 28, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:23 p.m.