Triple
T6087779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medo |
E135682
|
entity |
| Predicate | hasEmotionConnotation |
P4340
|
FINISHED |
| Object | affection |
—
|
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: affection | Statement: [Medo, hasEmotionConnotation, affection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmotionConnotation Context triple: [Medo, hasEmotionConnotation, affection]
-
A.
hasConnotation
chosen
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another entity.
-
B.
hasTypeOfEmotion
Indicates that an entity experiences, expresses, or is associated with a particular kind or category of emotion.
-
C.
intendedEmotion
Indicates the emotion that an action, expression, or communication is meant to evoke in its target, regardless of the actual emotion experienced.
-
D.
hasSentiment
Indicates that one entity expresses or embodies a particular emotional attitude, evaluation, or sentiment toward another entity or subject.
-
E.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0578bf2508190859c2dbd4c10b316 |
completed | March 22, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:12 p.m.