Triple
T27293369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allison Hunt |
E688689
|
entity |
| Predicate | causeOfEmotionalTraumaFor |
P84862
|
FINISHED |
| Object | Owen Hunt |
—
|
NE NERFINISHED |
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: Owen Hunt | Statement: [Allison Hunt, causeOfEmotionalTraumaFor, Owen Hunt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfEmotionalTraumaFor Context triple: [Allison Hunt, causeOfEmotionalTraumaFor, Owen Hunt]
-
A.
traumaTheme
Indicates that the relationship or context involves themes of trauma, such as psychological injury, distressing experiences, or their emotional and narrative impact.
-
B.
emotionalTrigger
chosen
Indicates that one entity causes or elicits an emotional response or reaction in another entity.
-
C.
trauma
Indicates that an entity has experienced a deeply distressing or harmful event or series of events that cause lasting psychological or emotional impact.
-
D.
causeOfWeepingEffect
Indicates that one entity is the reason or trigger that brings about another entity’s weeping or crying.
-
E.
causeOfViolence
Indicates that one entity is the reason, trigger, or source leading to the occurrence of violence involving another entity.
- 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 27, 2026, 11:17 a.m.