Triple
T25306463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Area Agencies on Aging in California |
E634493
|
entity |
| Predicate | hasNumberOfAgencies |
P163829
|
FINISHED |
| Object | 33 |
—
|
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: 33 | Statement: [Area Agencies on Aging in California, hasNumberOfAgencies, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAgencies Context triple: [Area Agencies on Aging in California, hasNumberOfAgencies, 33]
-
A.
hasNumberOfClinics
Indicates the quantity of clinics associated with or belonging to a given entity.
-
B.
hasNumberOfCompanies
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
C.
hasNumberOfRegionalOffices
Indicates the quantity of regional offices that an entity possesses or operates.
-
D.
managingAgencies
Indicates that one or more agencies are responsible for overseeing, directing, or administering the entity in question.
-
E.
numberOfSubordinateAgencies
Indicates the total count of agencies that are hierarchically subordinate to a given parent agency.
- 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_69e75a972c6481909bc11710e8d30a6c |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 21, 2026, 1:25 p.m.