Triple
T3178270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sub-Divisional Magistrate |
E66516
|
entity |
| Predicate | officeLocatedAt |
P29918
|
FINISHED |
| Object | sub-divisional headquarters |
—
|
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: sub-divisional headquarters | Statement: [Sub-Divisional Magistrate, officeLocatedAt, sub-divisional headquarters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeLocatedAt Context triple: [Sub-Divisional Magistrate, officeLocatedAt, sub-divisional headquarters]
-
A.
officeIsIn
chosen
Indicates that one office is located within or inside another specified place or building.
-
B.
agencyLocatedIn
Indicates that an agency is situated or based within a specific geographic or administrative location.
-
C.
mainOffice
Indicates that one location or office serves as the primary or central office for an organization or entity.
-
D.
headquartersLocation
Indicates the place where an organization’s main administrative center or principal office is located.
-
E.
employerHeadquarters
Indicates the location where an employer’s main corporate offices or central administrative operations are based.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada69db2088190baa1305892eb148a |
completed | March 8, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69ad9e02677c8190a21d93b1259b2761 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.