Triple
T8096737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iran Daylight Time |
E189003
|
entity |
| Predicate | observanceDependsOnLaw |
P80451
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Iran Daylight Time, observanceDependsOnLaw, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: observanceDependsOnLaw Context triple: [Iran Daylight Time, observanceDependsOnLaw, true]
-
A.
observance
Indicates the performance or maintenance of a practice, rule, or custom in accordance with prescribed or expected standards.
-
B.
observanceRequires
Indicates that carrying out a particular observance or practice is contingent upon, or must be accompanied by, the fulfillment of a specified requirement or condition.
-
C.
obeysLaw
Indicates that an entity follows, complies with, or acts in accordance with a specified law or set of laws.
-
D.
observanceVariesBy
Indicates that the way in which something is observed, practiced, or kept differs depending on a specified factor such as group, place, or time.
-
E.
observanceMayVaryByCountry
Indicates that the way something is observed, celebrated, or practiced can differ depending on the country.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb429319048190b612c8060a9a24d2 |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:30 p.m.