Triple
T37576313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Jim |
E934829
|
entity |
| Predicate | hasSpouseInPrank |
P198642
|
FINISHED |
| Object | Pam Beesly |
—
|
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: Pam Beesly | Statement: [Asian Jim, hasSpouseInPrank, Pam Beesly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpouseInPrank Context triple: [Asian Jim, hasSpouseInPrank, Pam Beesly]
-
A.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
hasSpouseInTVSeries
Indicates that one person is the spouse of another person within the context of a specific TV series.
-
D.
spouseOfProtagonistOf
Indicates that one entity is the spouse (married partner) of the main character (protagonist) of another entity, typically a narrative work.
-
E.
spouseInDuo
Indicates that two individuals are spouses who perform or appear together as a duo.
- F. None of above. chosen
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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
| PDg | Predicate description generation | batch_69fef8c2cdd881908c6f44e4dfa5ffd0 |
completed | May 9, 2026, 9:05 a.m. |
Created at: May 3, 2026, 4:17 p.m.