Triple
T28867759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan Swanson |
E729046
|
entity |
| Predicate | languageOfFilmCreditedFor |
P103547
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Logan Swanson, languageOfFilmCreditedFor, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFilmCreditedFor Context triple: [Logan Swanson, languageOfFilmCreditedFor, English]
-
A.
workLanguageOfTitle
Indicates the language in which a specific work or title is expressed or written.
-
B.
basedInFilmLanguage
Indicates that something is created, presented, or expressed using the language employed in a particular film.
-
C.
playedInLanguage
Indicates that an audiovisual work was performed or produced in a specified language.
-
D.
filmedInLanguage
chosen
Indicates that a film or video work was originally recorded using a particular spoken or signed language.
-
E.
areSpokenIn
Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
- 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_69f031a01cbc8190ba87270bb6fe4639 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fe5c1a502081909d4024e514309c8e |
completed | May 8, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69fe5a9df21c819087153f5d0bcaa987 |
completed | May 8, 2026, 9:50 p.m. |
Created at: April 28, 2026, 6:49 a.m.