Triple
T14044802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katherine Mayfair |
E337929
|
entity |
| Predicate | hasStoryArcElement |
P110520
|
FINISHED |
| Object | family secrets |
—
|
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: family secrets | Statement: [Katherine Mayfair, hasStoryArcElement, family secrets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStoryArcElement Context triple: [Katherine Mayfair, hasStoryArcElement, family secrets]
-
A.
notableStoryArc
Indicates that there exists a significant or prominent narrative storyline or plot development involving the subject.
-
B.
hasSiblingInStory
Indicates that one character in a narrative has at least one sibling who also appears within the same story.
-
C.
hasMainPlotElement
Indicates that one entity serves as a central or primary plot element within the narrative of another entity.
-
D.
hasAllyInStory
Indicates that one entity is portrayed as an ally or supportive partner of another entity within the context of a specific story or narrative.
-
E.
hasNarrativeEvent
chosen
Indicates that one entity includes, contains, or is associated with a specific narrative event within a story or sequence of events.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de312b94308190bd0961f5bc719c7b |
completed | April 14, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.