Triple
T8382388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fastest Skater |
E197723
|
entity |
| Predicate | isTimedIn |
P12450
|
FINISHED |
| Object | seconds |
—
|
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: seconds | Statement: [Fastest Skater, isTimedIn, seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTimedIn Context triple: [Fastest Skater, isTimedIn, seconds]
-
A.
checkInTime
chosen
Indicates the time at which an entity arrives at and formally registers its presence at a specified place or event.
-
B.
hasTimedEntry
Indicates that an entity is associated with an entry or access that is constrained or defined by a specific time or time period.
-
C.
isSetInTimePeriod
Indicates that an event, story, or situation takes place within a specified time period.
-
D.
timeStatus
Indicates the temporal state or condition of an event or entity relative to a reference time (e.g., past, present, future, ongoing, or scheduled).
-
E.
inOfficeDuring
Indicates that an entity holds or occupies an office or position throughout a specified time period.
- 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_69ca82f64c188190af4e1608036b865d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80ddc0f08190a90d4d9070bf713b |
completed | March 31, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69cb70cfe82881909fe374ba52649e84 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:02 p.m.