Triple
T30798943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Extremities |
E784311
|
entity |
| Predicate | impactOnAudience |
P150317
|
FINISHED |
| Object | intense emotional response |
—
|
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: intense emotional response | Statement: [Extremities, impactOnAudience, intense emotional response]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnAudience Context triple: [Extremities, impactOnAudience, intense emotional response]
-
A.
audienceImpact
chosen
Indicates how an action, message, or event affects, influences, or resonates with its intended audience.
-
B.
impactOnSubject
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
-
C.
exportImpact
Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
-
D.
impactOnMarket
Indicates the effect or influence that one factor, event, or action has on market conditions, behavior, or outcomes.
-
E.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 29, 2026, 8:42 p.m.