Triple
T8763001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Farquhar |
E208250
|
entity |
| Predicate | notableSeriesFocus |
P85244
|
FINISHED |
| Object | African American culture |
—
|
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: African American culture | Statement: [Ralph Farquhar, notableSeriesFocus, African American culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSeriesFocus Context triple: [Ralph Farquhar, notableSeriesFocus, African American culture]
-
A.
notableSeries
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
-
B.
notableOriginalSeries
Indicates that an entity is recognized as a significant or distinguished original series associated with another entity (such as a platform, creator, or franchise).
-
C.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
-
D.
notableSeriesContribution
Indicates that an entity has made a significant or distinguished contribution to a particular series (such as a publication, show, or collection).
-
E.
notableProgramType
Indicates that the subject is recognized for or associated with a particular type or category of program.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dfc85e481909a7ce80c5022e6e9 |
completed | March 31, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:40 p.m.