Triple
T17133999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Kiss |
E415788
|
entity |
| Predicate | hasPhotographerNationality |
P126233
|
FINISHED |
| Object | German-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: German-American | Statement: [The Kiss, hasPhotographerNationality, German-American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotographerNationality Context triple: [The Kiss, hasPhotographerNationality, German-American]
-
A.
hasCinematographerNationality
Indicates that a cinematographer is associated with a specific nationality.
-
B.
coverArtistNationality
Indicates the nationality of the artist who created the cover for a work.
-
C.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
D.
ownerNationality
Indicates that the owner of an entity has the specified nationality.
-
E.
hasParticipantNationality
Indicates that a participant in an event, activity, or relation has a specific nationality.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f02cbb7881908aa69c3443d149d5 |
completed | April 18, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69e3830192ac819091344a9e5a36c8c9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:36 a.m.