Triple
T12227032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Other Men’s Flowers |
E291377
|
entity |
| Predicate | hasCompilerNationality |
P103889
|
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: [Other Men’s Flowers, hasCompilerNationality, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompilerNationality Context triple: [Other Men’s Flowers, hasCompilerNationality, British]
-
A.
hasTranslatorNationality
Indicates that the nationality of the translator of a work or text is a specified country or cultural affiliation.
-
B.
hasParticipantNationality
Indicates that a participant in an event, activity, or relation has a specific nationality.
-
C.
hasOwnerNationalityStereotype
Indicates that an entity is associated with a stereotype about the nationality of its owner.
-
D.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
E.
builderNationality
Indicates the country or national affiliation of the entity that built or constructed 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d92468052c819090546f36d009a64f |
completed | April 10, 2026, 4:25 p.m. |
Created at: April 8, 2026, 9:51 p.m.