Triple
T20508498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 66 Steps |
E503495
|
entity |
| Predicate | currentApproximateNumberOfSteps |
P114447
|
FINISHED |
| Object | 65 |
—
|
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: 65 | Statement: [66 Steps, currentApproximateNumberOfSteps, 65]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentApproximateNumberOfSteps Context triple: [66 Steps, currentApproximateNumberOfSteps, 65]
-
A.
hasApproximateStepCount
chosen
Indicates that an entity is associated with an estimated or non-exact number of steps.
-
B.
stepCount
Indicates the number of discrete steps taken or required in a process, sequence, or movement.
-
C.
hasApproximateNumberOfRuns
Indicates that an entity is associated with a number of runs that is approximate rather than exact.
-
D.
approximateEstimation
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
-
E.
lapCountApproximate
Indicates that the recorded number of laps is an estimate rather than an exact, precise count.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dc8f3c881908ed2e0257a057e73 |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.