Triple
T35234410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelle Kwan’s “Salome” short program |
E1017330
|
entity |
| Predicate | programLengthCategory |
P155029
|
FINISHED |
| Object | short program |
—
|
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: short program | Statement: [Michelle Kwan’s “Salome” short program, programLengthCategory, short program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programLengthCategory Context triple: [Michelle Kwan’s “Salome” short program, programLengthCategory, short program]
-
A.
programLength
Indicates the duration or total length of a program, typically measured in time or size.
-
B.
courseLength
Indicates the duration or total length of a course, typically measured in units such as hours, weeks, or credits.
-
C.
workLengthCategory
chosen
Indicates the classification of a work based on its length or duration (e.g., short, medium, long).
-
D.
programScale
Indicates the relative size, scope, or extent of a program in terms of its capacity, reach, or level of operation.
-
E.
programPace
Indicates the speed or rate at which a program, course, or sequence of activities progresses over time.
- 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_69f76de12e4c8190bc46b71a32858356 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:02 p.m.