Triple
T160153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legislative Analyst’s Office |
E3264
|
entity |
| Predicate | workFocus |
P31
|
FINISHED |
| Object | state budget |
—
|
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: state budget | Statement: [Legislative Analyst’s Office, workFocus, state budget]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workFocus Context triple: [Legislative Analyst’s Office, workFocus, state budget]
-
A.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
B.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
associatedWork
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
-
D.
typeOfWork
Indicates the kind or category of work associated with or performed by an entity.
-
E.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25856d934819095460b2ea566eb6b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256623704819089d9eeefe05858ce |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.