Triple
T755371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Americans |
E15541
|
entity |
| Predicate | citizenshipStatusIncludes |
P13310
|
FINISHED |
| Object | U.S.-born citizens |
—
|
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: U.S.-born citizens | Statement: [Chinese Americans, citizenshipStatusIncludes, U.S.-born citizens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citizenshipStatusIncludes Context triple: [Chinese Americans, citizenshipStatusIncludes, U.S.-born citizens]
-
A.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
B.
hasCitizenshipRestriction
Indicates that there is a legal or policy-based limitation on who can obtain or hold citizenship in a given context.
-
C.
laterCitizenship
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
-
D.
citizenshipLinkedTo
chosen
Indicates that there is an established connection between an entity and a specific citizenship status, such as holding, sharing, or being associated with that citizenship.
-
E.
hasDualCitizenship
Indicates that a person is legally recognized as a citizen of two different countries at the same time.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a6693cbc8190a167e12a896d7ce7 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a50348088190873a1446db657a78 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.