Triple
T23629833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tablighi Jamaat |
E583574
|
entity |
| Predicate | majorEventCountry |
P153335
|
FINISHED |
| Object | Bangladesh |
—
|
NE NERFINISHED |
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: Bangladesh | Statement: [Tablighi Jamaat, majorEventCountry, Bangladesh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorEventCountry Context triple: [Tablighi Jamaat, majorEventCountry, Bangladesh]
-
A.
countryWithMultipleEvents
Indicates that a country is associated with more than one event within the given context or dataset.
-
B.
isMajorEventOf
Indicates that an event is a primary, significant, or defining occurrence within the context of another entity (such as a project, period, or process).
-
C.
majorEventContext
Indicates that one event occurs in the context of, or is significantly shaped by, a larger major event or overarching situation.
-
D.
largestEvent
Indicates that the referenced event is the one with the greatest magnitude, size, or extent among a specified set of events.
-
E.
notableInternationalEvents
Indicates that the subject is associated with significant events that have international relevance or impact.
- 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_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b1e71cac8190a3e1c04d7a5fffa1 |
completed | April 29, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f138b8c9248190b059bc38a9a50958 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 17, 2026, 6:47 p.m.