Triple
T36524790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statesman whiskey |
E900271
|
entity |
| Predicate | mediumOfTieIn |
P185811
|
FINISHED |
| Object | feature film |
—
|
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: feature film | Statement: [Statesman whiskey, mediumOfTieIn, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediumOfTieIn Context triple: [Statesman whiskey, mediumOfTieIn, feature film]
-
A.
mediumOfRecord
Indicates the primary medium or format through which an event, work, or information is officially documented or recorded.
-
B.
tieInWith
Indicates that one thing is connected, coordinated, or made consistent with another, often as part of a combined plan, theme, or schedule.
-
C.
mediumOfFame
Indicates the medium, field, or domain through which an entity became famous or gained public recognition.
-
D.
mediumDepictedIn
Indicates that a particular medium or material is represented, shown, or referenced within another work or depiction.
-
E.
mediatisedBy
Indicates that an entity’s communication or interaction is conveyed, shaped, or influenced through a particular medium or media channel rather than occurring directly.
- 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_69f76e5eedb88190a393b8c623f71dd7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c3705b5c81908c84004543a71c07 |
completed | May 3, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:11 p.m.