Triple
T34598177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicole Burnell |
E888374
|
entity |
| Predicate | emotionalStateAfterAccident |
P76175
|
FINISHED |
| Object | withdrawn |
—
|
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Phrase: withdrawn | Statement: [Nicole Burnell, emotionalStateAfterAccident, withdrawn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalStateAfterAccident Context triple: [Nicole Burnell, emotionalStateAfterAccident, withdrawn]
-
A.
psychologicalStateAfterCrime
Indicates the mental or emotional condition an individual experiences as a consequence of committing a crime.
-
B.
accidentState
Indicates the condition or status of an accident at a given point in time.
-
C.
emotionState
chosen
Indicates the emotional condition or feeling that an entity is currently experiencing.
-
D.
registrationStatusAfterAccident
Indicates the state of an entity’s registration following the occurrence of an accident.
-
E.
emotionalTrajectory
Indicates how an entity’s emotional state changes or progresses over time in relation to another entity or context.
- 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_69f349d3bfcc81909874c99e646fb3ea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7234bcaa48190ac970759d34e254a |
completed | May 3, 2026, 10:28 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:03 a.m.