Triple
T1410552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombay Time |
E31792
|
entity |
| Predicate | timeDifferenceWithIndianStandardTime |
P26621
|
FINISHED |
| Object | −00:39 |
—
|
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: −00:39 | Statement: [Bombay Time, timeDifferenceWithIndianStandardTime, −00:39]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeDifferenceWithIndianStandardTime Context triple: [Bombay Time, timeDifferenceWithIndianStandardTime, −00:39]
-
A.
differenceFromPakistanStandardTime
Indicates the time offset or deviation of a given time or timezone relative to Pakistan Standard Time.
-
B.
differenceFromBangladeshStandardTime
Indicates the time offset between a given time reference and Bangladesh Standard Time.
-
C.
timeDifferenceFromCentralStandard
Indicates the time offset between a given time reference and Central Standard Time (CST), typically expressed as the difference in hours or minutes.
-
D.
differenceFromChinaStandardTime
Indicates the time offset or deviation of something’s time setting relative to China Standard Time.
-
E.
differenceFromNepalTime
Indicates the time offset or deviation of a given time from the standard time observed in Nepal.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e0bfd08190a50820bc7585c28f |
completed | March 1, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69a4bf048b648190ab77d9b45cb4855f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:59 p.m.