Triple
T2570466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yom HaZikaron |
E57652
|
entity |
| Predicate | hasSirenDuration |
P12075
|
FINISHED |
| Object | one-minute siren in the evening |
—
|
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: one-minute siren in the evening | Statement: [Yom HaZikaron, hasSirenDuration, one-minute siren in the evening]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSirenDuration Context triple: [Yom HaZikaron, hasSirenDuration, one-minute siren in the evening]
-
A.
hasOfficialDuration
Indicates the formally defined length of time associated with an event, process, or entity.
-
B.
typicalRecordingDuration
Indicates the usual or standard length of time that something is recorded.
-
C.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
-
D.
showDuration
Indicates the length of time for which something is shown, displayed, or performed.
-
E.
interruptionDuration
chosen
Indicates the length of time for which an ongoing activity, process, or state is temporarily halted or disrupted.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd382928c8190b6316f3db48d8e73 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.