Triple
T33758466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobo (teddy bear) |
E865040
|
entity |
| Predicate | emotionalSignificanceFor |
P41499
|
FINISHED |
| Object | Montgomery Burns |
—
|
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: Montgomery Burns | Statement: [Bobo (teddy bear), emotionalSignificanceFor, Montgomery Burns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalSignificanceFor Context triple: [Bobo (teddy bear), emotionalSignificanceFor, Montgomery Burns]
-
A.
hasParticularSignificanceFor
chosen
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
B.
emotionalFocusOf
Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
-
C.
emotionalCoreOf
Indicates that one entity serves as the central source, essence, or primary driver of another entity’s emotional character or experience.
-
D.
hasEmotionalDimension
Indicates that something involves, expresses, or affects emotions as a significant aspect of its nature or impact.
-
E.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward 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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:45 a.m.