Triple
T16331605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deborah Kara Unger as Christine |
E396568
|
entity |
| Predicate | hasAmbiguous |
P122986
|
FINISHED |
| Object | motives |
—
|
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: motives | Statement: [Deborah Kara Unger as Christine, hasAmbiguous, motives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmbiguous Context triple: [Deborah Kara Unger as Christine, hasAmbiguous, motives]
-
A.
hasAmbiguousIdentity
Indicates that an entity’s identity is unclear, uncertain, or can be interpreted in multiple distinct ways.
-
B.
hasAmbiguousEnding
Indicates that the event, story, or situation concludes in a way that is open to multiple interpretations or lacks a clear, definitive resolution.
-
C.
isAmbiguousName
Indicates that a name can refer to multiple distinct entities or interpretations, making its reference unclear without additional context.
-
D.
hasUncertainAffinityWith
Indicates a relationship where the strength, nature, or existence of affinity between two entities is unclear, variable, or not confidently established.
-
E.
hasMultiple
Indicates that an entity is associated with more than one instance or occurrence of another related entity.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4dfd9688190a749e48ebc055baf |
completed | April 17, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.