Triple
T34641998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrison Ford as Dr. Norman Spencer |
E889584
|
entity |
| Predicate | keyStoryElement |
P112925
|
FINISHED |
| Object | extramaritalAffair |
—
|
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: extramaritalAffair | Statement: [Harrison Ford as Dr. Norman Spencer, keyStoryElement, extramaritalAffair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyStoryElement Context triple: [Harrison Ford as Dr. Norman Spencer, keyStoryElement, extramaritalAffair]
-
A.
storyElement
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
-
B.
coreNarrative
Indicates the primary storyline or central sequence of events that forms the main thread of a narrative.
-
C.
storylineEvent
Indicates that one event occurs as a distinct step or component within a larger narrative or storyline.
-
D.
notableFeatureInStory
chosen
Indicates that a particular feature, element, or characteristic plays a significant or prominent role within a story.
-
E.
knowledgeSourceInStory
Indicates that a particular source or origin of information is referenced or used within the context of a story.
- 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_69f349d724848190b63ad3407e0006d9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72292f4388190a72cd79d37a244e7 |
completed | May 3, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:04 a.m.