Triple
T16635999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Serious Man |
E404205
|
entity |
| Predicate | openingSequenceLanguage |
P123673
|
FINISHED |
| Object | Yiddish |
—
|
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: Yiddish | Statement: [A Serious Man, openingSequenceLanguage, Yiddish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingSequenceLanguage Context triple: [A Serious Man, openingSequenceLanguage, Yiddish]
-
A.
openingSequenceFormat
Indicates the specific structural or stylistic format used for an opening sequence in a work or presentation.
-
B.
openingSequenceType
Indicates the specific kind or category of an opening sequence associated with an entity or event.
-
C.
languageBegins
Indicates that a particular language starts to be used, recognized, or becomes relevant at a specific point in time or context.
-
D.
openingLine
Indicates that one entity is the first line or initial statement that begins another entity, such as a text, speech, or conversation.
-
E.
openingNarrationBy
Indicates that an entity serves as the narrator delivering the opening narration for another entity (such as a work or production).
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e999d48190bff680040dbc883d |
completed | April 18, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.