Triple
T8270654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ladies' singles figure skating |
E193418
|
entity |
| Predicate | freeSkateDuration |
P82416
|
FINISHED |
| Object | 4 minutes (plus 10 seconds) maximum |
—
|
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: 4 minutes (plus 10 seconds) maximum | Statement: [ladies' singles figure skating, freeSkateDuration, 4 minutes (plus 10 seconds) maximum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: freeSkateDuration Context triple: [ladies' singles figure skating, freeSkateDuration, 4 minutes (plus 10 seconds) maximum]
-
A.
banDurationApproximate
Indicates that the duration of a ban is known only approximately rather than as an exact, precise time period.
-
B.
isAccessibleForFreeParking
Indicates that a location or facility can be used for parking without any cost.
-
C.
concessionDuration
Indicates the length of time for which a concession, such as a granted right or privilege, remains valid or in effect between parties.
-
D.
freeSection
Indicates that a section or segment is available without cost or restrictions to the user.
-
E.
firstFreeAscentDuration
Indicates the length of time taken to complete the first free ascent of a route or climb.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb795243fc8190a66afef7476e1147 |
completed | March 31, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:50 p.m.