Triple
T1582911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Insurance Commissioner of California |
E34005
|
entity |
| Predicate | officeCreationYear |
P32879
|
FINISHED |
| Object | 1988 |
—
|
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: 1988 | Statement: [Insurance Commissioner of California, officeCreationYear, 1988]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeCreationYear Context triple: [Insurance Commissioner of California, officeCreationYear, 1988]
-
A.
incorporationYear
Indicates the calendar year in which an organization or entity was formally incorporated or legally established.
-
B.
yearOfManufacture
Indicates the specific calendar year in which an item was produced or manufactured.
-
C.
accessionYear
Indicates the calendar year in which an item, record, or entity was formally added to or registered within a collection, system, or institution.
-
D.
purchaseYear
Indicates the calendar year in which a purchase or acquisition of something took place.
-
E.
yearOfUse
Indicates the specific year during which something was in use or actively utilized.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abacfb1144819080c5687175aba1e1 |
completed | March 7, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69aa61b0f5bc8190b1dc272990a59c13 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69abacf991148190b20521c063f93bfd |
completed | March 7, 2026, 4:43 a.m. |
Created at: March 4, 2026, 7:27 p.m.