Triple
T36694760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interlude: I Got So Much Magic, You Can Have It |
E906055
|
entity |
| Predicate | creatorNationalityContext |
P200853
|
FINISHED |
| Object | African-American cultural context |
—
|
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 cultural context | Statement: [Interlude: I Got So Much Magic, You Can Have It, creatorNationalityContext, African-American cultural context]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creatorNationalityContext Context triple: [Interlude: I Got So Much Magic, You Can Have It, creatorNationalityContext, African-American cultural context]
-
A.
creatorNationality
Indicates that the creator of an entity has a specified national affiliation or citizenship.
-
B.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
C.
producerNationality
Indicates that a producer has a particular national affiliation or country of origin.
-
D.
sourceWorkNationality
Indicates that a work or source is associated with a particular nationality or country of origin.
-
E.
coArtistNationality
Indicates that two artists who have collaborated share the same nationality.
- 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_69f76e70d2448190bdd3ce781ba971c5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffb1f0b03c81909ddb81f07ce74e88 |
completed | May 9, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ffb1662b2481908582e0612744f4c5 |
completed | May 9, 2026, 10:12 p.m. |
| PDg | Predicate description generation | batch_69ffb1f001948190a63c493b596a97b9 |
completed | May 9, 2026, 10:15 p.m. |
Created at: May 3, 2026, 4:12 p.m.