Triple
T35014081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mouse |
E1010006
|
entity |
| Predicate | commonPlotMotif |
P41002
|
FINISHED |
| Object | small character defeating larger foe |
—
|
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: small character defeating larger foe | Statement: [Mouse, commonPlotMotif, small character defeating larger foe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonPlotMotif Context triple: [Mouse, commonPlotMotif, small character defeating larger foe]
-
A.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
B.
commonMotifRegion
Indicates that two or more entities share a recurring motif within the same spatial or contextual region.
-
C.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
-
D.
transformationMotif
Indicates a recurring pattern or theme in which one entity undergoes a change in form, state, or identity in relation to another.
-
E.
numberOfMotifs
Indicates the count of distinct motifs associated with or contained within a given 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fec8aef1d8819094c7fd7074038e6b |
completed | May 9, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69fec639876481908efd84a3631a4271 |
completed | May 9, 2026, 5:29 a.m. |
Created at: May 3, 2026, 4:01 p.m.