Triple
T24195926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy War (BYU–Utah football rivalry) |
E599834
|
entity |
| Predicate | hasEmotionalIntensity |
P155135
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Holy War (BYU–Utah football rivalry), hasEmotionalIntensity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmotionalIntensity Context triple: [Holy War (BYU–Utah football rivalry), hasEmotionalIntensity, high]
-
A.
hasTypeOfEmotion
Indicates that an entity experiences, expresses, or is associated with a particular kind or category of emotion.
-
B.
emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
-
C.
emotionalTrait
Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
-
D.
requiresEmotion
Indicates that one entity’s occurrence, validity, or performance depends on the presence or experience of a particular emotion in another entity.
-
E.
emotionalScope
Indicates the range or extent of emotions involved or affected within a given relationship or situation.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e24ad83c819084ac9e34d2cc2120 |
completed | April 29, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c9834064819082024233d9c6f98f |
completed | April 29, 2026, 9:04 a.m. |
Created at: April 17, 2026, 11:36 p.m.