Triple
T23350043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamie Fields |
E591979
|
entity |
| Predicate | citizenshipInStory |
P15237
|
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: [Jamie Fields, citizenshipInStory, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citizenshipInStory Context triple: [Jamie Fields, citizenshipInStory, American]
-
A.
nationalityInStory
chosen
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
B.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
C.
citizenshipContext
Indicates the legal or social circumstances under which an entity holds or is granted citizenship in a particular state or jurisdiction.
-
D.
isCitizenOf
Indicates that a person holds legal nationality or citizenship status in a particular country or state.
-
E.
fictionalCitizenship
Indicates that an entity is recognized as a citizen of a fictional or imaginary polity, realm, or jurisdiction.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a132da08190b30de610d34c96cc |
completed | April 29, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:19 p.m.