Triple
T18233228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sketchbook |
E436597
|
entity |
| Predicate | mainPerformerCitizenship |
P98308
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Sketchbook, mainPerformerCitizenship, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPerformerCitizenship Context triple: [Sketchbook, mainPerformerCitizenship, American]
-
A.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
B.
isCitizenOf
chosen
Indicates that a person holds legal nationality or citizenship status in a particular country or state.
-
C.
hasTypicalCitizenship
Indicates that an entity is generally or commonly a citizen of a specified country or jurisdiction.
-
D.
hasHostCitizenship
Indicates that an entity holds citizenship in, or is a citizen of, a specified host country or jurisdiction.
-
E.
citizenshipType
Indicates the specific legal category or status of an individual's citizenship in relation to a state or country.
- F. None of above.
Provenance (3 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b512a88190aa493b0793ab28b3 |
completed | April 19, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:33 a.m.