Triple
T26893374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | মধু কবি |
E677836
|
entity |
| Predicate | referredPersonReligion |
P45
|
FINISHED |
| Object | খ্রিস্টান (পরবর্তীকালে ধর্মান্তরিত) |
—
|
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: খ্রিস্টান (পরবর্তীকালে ধর্মান্তরিত) | Statement: [মধু কবি, referredPersonReligion, খ্রিস্টান (পরবর্তীকালে ধর্মান্তরিত)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: referredPersonReligion Context triple: [মধু কবি, referredPersonReligion, খ্রিস্টান (পরবর্তীকালে ধর্মান্তরিত)]
-
A.
declaredReligion
Indicates that an entity has formally stated or reported a particular religious affiliation.
-
B.
relationshipToReligion
Indicates the nature or type of connection an entity has to a religion, such as affiliation, stance, or involvement.
-
C.
associatedReligionText
Indicates that there is a textual work (such as a scripture or religious document) that is specifically associated with, or pertains to, a given religion.
-
D.
religiousAffiliation
chosen
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
E.
associatedReligionRole
Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 27, 2026, 5:46 a.m.