Triple
T5140393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dig-Dig-Dig Dig For Your Dinner |
E115932
|
entity |
| Predicate | basedInFilmEra |
P26306
|
FINISHED |
| Object | classic Hollywood |
—
|
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: classic Hollywood | Statement: [Dig-Dig-Dig Dig For Your Dinner, basedInFilmEra, classic Hollywood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedInFilmEra Context triple: [Dig-Dig-Dig Dig For Your Dinner, basedInFilmEra, classic Hollywood]
-
A.
filmEra
chosen
Indicates the historical or stylistic period in which a film was produced or to which its cinematic style belongs.
-
B.
filmStudioEra
Indicates the historical period or era during which a particular film studio was active or most influential.
-
C.
filmSettingDecade
Indicates the decade in which the events or primary narrative of a film are set.
-
D.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
E.
filmDebutPeriod
Indicates the time period during which an entity (typically a person) made their first appearance in a film.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.