Triple
T17199639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Foreman |
E417442
|
entity |
| Predicate | nationalityCoverIdentity |
P92867
|
FINISHED |
| Object | British |
—
|
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: British | Statement: [Susan Foreman, nationalityCoverIdentity, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityCoverIdentity Context triple: [Susan Foreman, nationalityCoverIdentity, British]
-
A.
nationalityInCoverIdentity
chosen
Indicates that an entity’s assumed or cover identity is associated with a particular nationality.
-
B.
hasNationalIdentity
Indicates that an entity possesses or is associated with a particular national identity or nationality.
-
C.
citizenshipDocument
Indicates that there exists an official document that certifies or proves an entity’s citizenship status with respect to a state or country.
-
D.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
E.
possibleCountryOfCitizenship
Indicates that an entity could plausibly be a country in which the person or agent may hold, or be eligible to hold, 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42daddcd08190a82f36c940bf3f7b |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.