Triple
T19394273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian MacAlpin |
E485145
|
entity |
| Predicate | climacticAct |
P136284
|
FINISHED |
| Object | bakes and presents a woman-shaped cake |
—
|
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: bakes and presents a woman-shaped cake | Statement: [Marian MacAlpin, climacticAct, bakes and presents a woman-shaped cake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: climacticAct Context triple: [Marian MacAlpin, climacticAct, bakes and presents a woman-shaped cake]
-
A.
typeOfClimax
Indicates the specific kind or category of climax that characterizes an event, narrative, or process.
-
B.
climaxEvents
Indicates that the related events represent the peak or most intense turning point within a larger sequence or narrative.
-
C.
hasClimaxAt
Indicates that an event, narrative, or process reaches its most intense or decisive point at a specified time, place, or segment.
-
D.
dramaticClimaxInvolvement
Indicates involvement in the pivotal, most intense turning point or climax of a dramatic work or narrative.
-
E.
climaxLocation
Indicates the place or setting where the most intense or pivotal moment of an event, narrative, or process occurs.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b47630881909ba390888b8779f6 |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69e50213571881909cd7543a43b51986 |
completed | April 19, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.