Triple
T21677076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naturalization Act of 1795 |
E534997
|
entity |
| Predicate | citizenshipConferredBy |
P81741
|
FINISHED |
| Object | court order after meeting statutory requirements |
—
|
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: court order after meeting statutory requirements | Statement: [Naturalization Act of 1795, citizenshipConferredBy, court order after meeting statutory requirements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citizenshipConferredBy Context triple: [Naturalization Act of 1795, citizenshipConferredBy, court order after meeting statutory requirements]
-
A.
grantedCitizenshipBy
chosen
Indicates that one entity has officially conferred citizenship status upon another entity.
-
B.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
C.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
D.
citizenshipBasedOn
Indicates that an entity’s citizenship is determined or derived from another specified factor, condition, or relationship.
-
E.
citizenshipGrantedYear
Indicates the specific year in which an entity was officially granted citizenship.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a105b888190820b894d16c1ab77 |
completed | April 27, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:42 p.m.