Triple
T23754790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kishoreganj District |
E587074
|
entity |
| Predicate | hasNumberOfUnionCouncils |
P153566
|
FINISHED |
| Object | 100+ |
—
|
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: 100+ | Statement: [Kishoreganj District, hasNumberOfUnionCouncils, 100+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfUnionCouncils Context triple: [Kishoreganj District, hasNumberOfUnionCouncils, 100+]
-
A.
numberOfRegionalCouncils
Indicates the total count of regional councils associated with a given entity.
-
B.
hasNumberOfSubdistricts
Indicates the relationship specifying how many subdistricts are associated with a given entity.
-
C.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
D.
hasUpazila
Indicates a relationship where a larger administrative region or district includes or is associated with one or more upazilas (sub-districts).
-
E.
hasCouncilAreaPart
Indicates that one council area includes another council area as a constituent part within its administrative or geographic boundaries.
- 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_69e2490a0eec81908cdef8a862828d7a |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bdab86108190becd7f27650082cc |
completed | April 29, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:13 p.m.