Triple
T25174080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Budget and Management (Philippines) |
E630398
|
entity |
| Predicate | formedAsDepartment |
P169510
|
FINISHED |
| Object | 1986 |
—
|
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: 1986 | Statement: [Department of Budget and Management (Philippines), formedAsDepartment, 1986]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formedAsDepartment Context triple: [Department of Budget and Management (Philippines), formedAsDepartment, 1986]
-
A.
basedInDepartment
Indicates that an entity operates or has its primary affiliation within a specific department.
-
B.
formerDepartment
Indicates that one entity previously served as a department or subunit of another entity but no longer holds that status.
-
C.
formedAsMinistry
Indicates that an organization or body was created or established in the form of a ministry.
-
D.
worksInDepartment
Indicates that an entity is employed in and performs their job duties within a particular department.
-
E.
laterDepartment
Indicates that one department occurs or is considered after another in a defined ordering or sequence.
- 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_69e75a87c9b88190ab60731902a99750 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f67fc237608190b6542b56038a7fe4 |
completed | May 2, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 21, 2026, 12:21 p.m.