Triple
T12812995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Reply to Hayne |
E306316
|
entity |
| Predicate | circaDuration |
P106508
|
FINISHED |
| Object | several hours |
—
|
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: several hours | Statement: [Second Reply to Hayne, circaDuration, several hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circaDuration Context triple: [Second Reply to Hayne, circaDuration, several hours]
-
A.
eraDuration
Indicates the length of time that a particular era or period spans.
-
B.
intendedDuration
Indicates the planned or expected length of time for which an action, event, or state is meant to occur or remain in effect.
-
C.
banDurationApproximate
Indicates that the duration of a ban is known only approximately rather than as an exact, precise time period.
-
D.
lengthInMinutes
Indicates the duration of something expressed as a number of minutes.
-
E.
durationCategory
Indicates the classification of an event or state based on how long it lasts, grouping it into a specific duration range or type.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9adcf08190a12801adcc613477 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d88be0481908c311f1e71b61e70 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:31 p.m.