Triple
T32403430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Commissioner of Lakshmipur |
E828011
|
entity |
| Predicate | isRoleInOrganization |
P13957
|
FINISHED |
| Object | district administration of Lakshmipur |
—
|
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: district administration of Lakshmipur | Statement: [Deputy Commissioner of Lakshmipur, isRoleInOrganization, district administration of Lakshmipur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRoleInOrganization Context triple: [Deputy Commissioner of Lakshmipur, isRoleInOrganization, district administration of Lakshmipur]
-
A.
hasPositionInOrganization
Indicates that an entity holds a specific role, job, or position within a particular organization.
-
B.
hasOrganizationalRole
chosen
Indicates that an entity holds a specific role, position, or function within an organization.
-
C.
hasNameInOrganization
Indicates that an entity is known by a particular name within the context of a specific organization.
-
D.
isMemberOfSameOrganization
Indicates that two entities belong to, or are affiliated with, the same organization.
-
E.
appearsInOrganization
Indicates that an entity is present, featured, or participates within a particular organization.
- 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_69f34919342c8190a4c3bf35a90d4e58 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c2451e108190a73ccfdc99203d55 |
completed | May 3, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:53 a.m.