Triple
T35606154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Grimaldi |
E1028897
|
entity |
| Predicate | hasLoverInStory |
P192977
|
FINISHED |
| Object | Sheri |
—
|
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: Sheri | Statement: [Jack Grimaldi, hasLoverInStory, Sheri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoverInStory Context triple: [Jack Grimaldi, hasLoverInStory, Sheri]
-
A.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
B.
hasYoungLoverCharacter
Indicates that an entity is involved in a romantic or intimate relationship with a significantly younger lover character.
-
C.
hasFictionalRomanticInterest
chosen
Indicates that one entity is portrayed as having a romantic attraction or interest toward another entity within a fictional context.
-
D.
hasFianceeOfSonAsLover
Indicates that a person is in a romantic or sexual relationship with their son’s fiancée.
-
E.
hasRomanticEntanglementInPlot
Indicates that a romantic relationship or involvement between characters is a significant element within the narrative plot.
- 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_69f76e0653ec81909b1b813c126c6574 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff2d22ffb48190ae58ddf3c7e02869 |
completed | May 9, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_69ff2ac2e1c4819096cc64e94aef2ff0 |
completed | May 9, 2026, 12:38 p.m. |
Created at: May 3, 2026, 4:05 p.m.