Triple
T22422898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sext |
E554293
|
entity |
| Predicate | approximateTimeRange |
P125927
|
FINISHED |
| Object | 11:00–13:00 |
—
|
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: 11:00–13:00 | Statement: [Sext, approximateTimeRange, 11:00–13:00]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTimeRange Context triple: [Sext, approximateTimeRange, 11:00–13:00]
-
A.
timePeriodApproximation
Indicates that the associated time period is an estimate or approximation rather than an exact, precise value.
-
B.
timeframeApproximate
chosen
Indicates that the time period associated with an event or relation is not exact but only roughly or loosely specified.
-
C.
timeStartApprox
Indicates that the associated event or state begins at an approximate, rather than exact, point in time.
-
D.
dateApproximate
Indicates that the associated date is not exact but estimated or approximate rather than precisely known.
-
E.
timePeriodEndApprox
Indicates that the associated time period ends at an approximate, rather than exact, point in 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2a1a3c8190a649ee4df2429e69 |
completed | April 29, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:47 p.m.