Triple
T16983672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Riley |
E412005
|
entity |
| Predicate | hasMultipleEndings |
P55743
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Jessica Riley, hasMultipleEndings, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleEndings Context triple: [Jessica Riley, hasMultipleEndings, true]
-
A.
hasAmbiguousEnding
Indicates that the event, story, or situation concludes in a way that is open to multiple interpretations or lacks a clear, definitive resolution.
-
B.
hasUnfinishedEnding
Indicates that an entity concludes in an incomplete, unresolved, or open-ended manner rather than reaching a fully finished state.
-
C.
alternateEnding
chosen
Indicates that one version of a work provides a different conclusion or final sequence of events compared to the original or primary ending.
-
D.
hasTragicEnding
Indicates that the event, story, or situation concludes with a sorrowful, disastrous, or otherwise deeply unfortunate outcome.
-
E.
hasHappyEnding
Indicates that the event, story, or situation concludes with a positive, satisfying, or favorable outcome for the involved 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d188ede48190baead48aac84c78d |
completed | April 18, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.