Triple
T23882609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Rifkin |
E600243
|
entity |
| Predicate | writingRegion |
P153930
|
FINISHED |
| Object | Southern California |
—
|
NE NERFINISHED |
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: Southern California | Statement: [Alan Rifkin, writingRegion, Southern California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingRegion Context triple: [Alan Rifkin, writingRegion, Southern California]
-
A.
writingSystemScope
Indicates the range or extent of content, languages, or contexts to which a particular writing system applies or is used.
-
B.
writingComponent
Indicates that one entity is a written part or element that contributes to the composition or structure of another entity.
-
C.
writesLanguage
Indicates that an entity produces written content in a particular language.
-
D.
writtenDuring
Indicates that the creation or authorship of something took place within a specified time period or historical event.
-
E.
writingOutput
Indicates that one entity produces or generates written content as an output, typically as the result of a writing or text-creation process.
- 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ccfaef348190b4820b6f3648c60c |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:24 p.m.