Triple
T27409117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deanna Dwyer |
E692091
|
entity |
| Predicate | nationalityOfRealName |
P78054
|
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: [Deanna Dwyer, nationalityOfRealName, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityOfRealName Context triple: [Deanna Dwyer, nationalityOfRealName, American]
-
A.
nationalityOfRealIdentity
Indicates that a specified nationality is the real-world national affiliation of an entity’s true identity.
-
B.
nationalityOfPersonReferredTo
chosen
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
C.
nationalityOfActor
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
D.
namesakeNationality
Indicates that one entity has the same nationality as the person or entity after whom it is named.
-
E.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
- 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_69ef5205fc808190ad3efc5525b8e6d6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 27, 2026, 12:31 p.m.