Triple
T11228558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald O'Hara |
E265758
|
entity |
| Predicate | nationalityAfterEmigration |
P97942
|
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: [Gerald O'Hara, nationalityAfterEmigration, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityAfterEmigration Context triple: [Gerald O'Hara, nationalityAfterEmigration, American]
-
A.
countryOfEmigration
Indicates the country from which a person or group has emigrated or moved away.
-
B.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
C.
formerCitizenship
Indicates that an entity previously held, but no longer holds, citizenship in a specified country or state.
-
D.
nationalityAtDeath
Indicates the country or national affiliation a person held at the time of their death.
-
E.
countryOfNaturalization
Indicates that an entity became a citizen of the specified country through the legal process of naturalization.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e900fbcc8190a3177f8a73564433 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d75cfbbb188190861efd5d94fe27da |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.