Triple
T7333627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iran Standard Time |
E169067
|
entity |
| Predicate | usedOnMainland |
P67139
|
FINISHED |
| Object | entire territory of Iran |
—
|
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: entire territory of Iran | Statement: [Iran Standard Time, usedOnMainland, entire territory of Iran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnMainland Context triple: [Iran Standard Time, usedOnMainland, entire territory of Iran]
-
A.
appliesToMainland
chosen
Indicates that something is relevant or applicable specifically to the mainland portion of a territory, excluding its islands or overseas areas.
-
B.
usedOnIslands
Indicates that something is utilized or applied specifically on islands.
-
C.
usesOnLand
Indicates that one entity employs or operates another entity specifically in a land-based context.
-
D.
connectedToMainlandBy
Indicates that one landmass or area is physically linked to a mainland, typically via a bridge, causeway, or other continuous connection.
-
E.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
- 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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.