Triple
T11995486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Thewlis as Paul Verlaine |
E285517
|
entity |
| Predicate | basedOnNationality |
P102785
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [David Thewlis as Paul Verlaine, basedOnNationality, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnNationality Context triple: [David Thewlis as Paul Verlaine, basedOnNationality, French]
-
A.
riddenByNationality
Indicates that something being ridden (such as an animal or vehicle) is ridden by a rider of a specified nationality.
-
B.
appliesToPersonNationality
Indicates that something is relevant or applicable specifically to a person’s nationality.
-
C.
ledByNationality
Indicates that an entity (such as an organization, group, or project) is led or headed by a person or group of a specified nationality.
-
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.
includedNationality
Indicates that one entity’s set of nationalities contains or encompasses the nationality of another entity.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d903a8695c8190bfa9d7ca50834f9f |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.