Triple
T25902475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bowling |
E652654
|
entity |
| Predicate | featuresCharacterTakingBoys |
P93957
|
FINISHED |
| Object | Lois |
—
|
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: Lois | Statement: [Bowling, featuresCharacterTakingBoys, Lois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterTakingBoys Context triple: [Bowling, featuresCharacterTakingBoys, Lois]
-
A.
childCharacter
Indicates that one entity is a child version or child role of another character entity.
-
B.
featuresCharacterWith
chosen
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
C.
studentCharacter
Indicates that one entity has the role or qualities of a student in relation to another entity, typically within an educational or learning context.
-
D.
teenageCharacter
Indicates that the character is in their teenage years, typically between ages 13 and 19.
-
E.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: April 22, 2026, 8:26 a.m.