Triple
T33986007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comedies and Proverbs |
E871410
|
entity |
| Predicate | hasProverbialMotto |
P33142
|
FINISHED |
| Object | each film associated with a proverb |
—
|
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: each film associated with a proverb | Statement: [Comedies and Proverbs, hasProverbialMotto, each film associated with a proverb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProverbialMotto Context triple: [Comedies and Proverbs, hasProverbialMotto, each film associated with a proverb]
-
A.
hasMottoLikeFunction
chosen
Indicates that something serves a role or function similar to a motto, typically expressing a guiding principle, slogan, or core message.
-
B.
hasMottoSymbol
Indicates that an entity’s motto is represented or accompanied by a particular symbol.
-
C.
usesMotto
Indicates that one entity adopts or employs a particular motto as its guiding phrase or slogan.
-
D.
hasMottoScript
Indicates that an entity’s motto is written or expressed in a particular writing system or script.
-
E.
hasMottoDepiction
Indicates that something visually represents or depicts the motto associated with an 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a021706e21c81909b83e2b4d9c4130c |
completed | May 11, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_6a0216861214819097d2177755bc19d7 |
completed | May 11, 2026, 5:48 p.m. |
Created at: May 1, 2026, 1:50 a.m.