Triple
T582685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gujarat |
E15090
|
entity |
| Predicate | timeZone |
P109
|
FINISHED |
| Object | Indian Standard Time |
E5066
|
NE 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: Indian Standard Time | Statement: [Gujarat, timeZone, Indian Standard Time]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Indian Standard Time Context triple: [Gujarat, timeZone, Indian Standard Time]
-
A.
Indian Standard Time
chosen
Indian Standard Time is the time zone used throughout India, set at UTC+5:30.
-
B.
Pakistan Standard Time
Pakistan Standard Time is the time zone used throughout Pakistan, corresponding to UTC+5 hours.
-
C.
Sri Lanka Standard Time
Sri Lanka Standard Time is the time zone used throughout Sri Lanka, set at UTC+5:30.
-
D.
Madras Time
Madras Time was a former local time standard used in the Madras (now Chennai) region of India before the adoption of a unified national time zone.
-
E.
Iran Standard Time
Iran Standard Time is the time zone used throughout Iran, set at UTC+3:30 and observed in cities such as Tehran.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b85becc8190b4d98c00e5fa7c04 |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a50e25f4e4819081c8973b0f24dec0 |
completed | March 2, 2026, 4:12 a.m. |
Created at: March 1, 2026, 7:33 p.m.