Triple
T15005165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taranganba |
E377689
|
entity |
| Predicate | taranganbaStateSchool_instanceOf |
P72238
|
FINISHED |
| Object | government primary school |
—
|
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: government primary school | Statement: [Taranganba, taranganbaStateSchool_instanceOf, government primary school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: taranganbaStateSchool_instanceOf Context triple: [Taranganba, taranganbaStateSchool_instanceOf, government primary school]
-
A.
schoolBelongsTo
Indicates that a particular school is owned by, affiliated with, or under the authority or jurisdiction of a specific organization, institution, or administrative entity.
-
B.
schoolRoll
Indicates the official list or record of students enrolled in a particular school or class.
-
C.
hasSchoolBoardType
Indicates the specific governance or organizational structure type of a school board associated with an educational institution or district.
-
D.
schoolClassification
chosen
Indicates how a school is categorized within an educational system, such as by level, type, or other official classification.
-
E.
schoolOf
Indicates that an educational institution is the one where a person studied, worked, or is otherwise academically affiliated.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7322b5c81909089cbbf816e1436 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.