Triple
T37853962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Sweeney |
E944131
|
entity |
| Predicate | significantOtherInSeries |
P143936
|
FINISHED |
| Object | Jessica Day |
—
|
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: Jessica Day | Statement: [Sam Sweeney, significantOtherInSeries, Jessica Day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantOtherInSeries Context triple: [Sam Sweeney, significantOtherInSeries, Jessica Day]
-
A.
romanticPartnerInSeries
chosen
Indicates that one character is portrayed as a romantic partner of another character within the context of a specific series or narrative.
-
B.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
C.
romanticPartnerInSpinOff
Indicates that two characters are depicted as romantic partners specifically within a spin-off work, rather than (or in addition to) the original series.
-
D.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69f76eed4d9c81908b1b71ba9e3b61fe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: May 3, 2026, 4:19 p.m.