Triple
T33200834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jashn-E-Bahaara |
E849894
|
entity |
| Predicate | setInFilmPeriod |
P93599
|
FINISHED |
| Object | Mughal era |
—
|
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: Mughal era | Statement: [Jashn-E-Bahaara, setInFilmPeriod, Mughal era]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setInFilmPeriod Context triple: [Jashn-E-Bahaara, setInFilmPeriod, Mughal era]
-
A.
filmingPeriod
Indicates the time span during which the filming of something takes place.
-
B.
setInFictionalYear
Indicates that the events or narrative of a work are situated in a specified fictional or non-real calendar year.
-
C.
settingTimeRelativeToFilms
Indicates the temporal relationship of one film’s setting relative to the settings of other films (e.g., earlier, later, or at the same time).
-
D.
appearsInTimePeriodDepicted
Indicates that something is present or occurs within the specific time period that is depicted or represented.
-
E.
settingDepictedPeriod
chosen
Indicates the historical or temporal period in which the setting of something (e.g., a work or scene) is depicted.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:29 a.m.