Triple
T29787858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Englishman in New York |
E756311
|
entity |
| Predicate | isInEnglishPopCulture |
P80267
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [An Englishman in New York, isInEnglishPopCulture, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInEnglishPopCulture Context triple: [An Englishman in New York, isInEnglishPopCulture, true]
-
A.
hasCulturalReference
Indicates that one entity makes reference to, draws from, or is associated with the cultural content, symbols, or traditions represented by another entity.
-
B.
hasEnduringPopCulturePresence
chosen
Indicates that the subject continues to appear in, influence, or be referenced within popular culture over an extended period of time.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
E.
languageOfSurroundingCulture
Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with another entity.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f674abd4bc81908993a7677238b80c |
completed | May 2, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:10 p.m.