Triple
T33758450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobo (teddy bear) |
E865040
|
entity |
| Predicate | hasNotableSceneWith |
P128577
|
FINISHED |
| Object | Maggie Simpson |
E203648
|
NE 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: Maggie Simpson | Statement: [Bobo (teddy bear), hasNotableSceneWith, Maggie Simpson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSceneWith Context triple: [Bobo (teddy bear), hasNotableSceneWith, Maggie Simpson]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
notableSceneAssociation
chosen
Indicates an association between an entity and a notable or memorable scene in which it prominently appears or plays a significant role.
-
C.
hasCutscenesBy
Indicates that one entity (such as a game or media work) contains cutscenes that were created, directed, or authored by another entity.
-
D.
hasRegionalScene
Indicates that something possesses or is associated with a specific regional scene, such as a localized cultural, artistic, or social milieu.
-
E.
hasLastSceneWith
Indicates that two entities share the same final scene or appearance together within a work or sequence.
- F. None of above.
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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01f4d954e08190aff3756955212d67 |
completed | May 11, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37d92d48a88190b2c9f63a9ca0cce1 |
completed | June 21, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_6a01edadb9248190be592287530740a5 |
completed | May 11, 2026, 2:54 p.m. |
Created at: May 1, 2026, 1:45 a.m.