Triple
T36196123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adding Machine: A Musical |
E1047128
|
entity |
| Predicate | originalPlayGenre |
P115706
|
FINISHED |
| Object | expressionist drama |
—
|
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: expressionist drama | Statement: [Adding Machine: A Musical, originalPlayGenre, expressionist drama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalPlayGenre Context triple: [Adding Machine: A Musical, originalPlayGenre, expressionist drama]
-
A.
primarySourceGenre
chosen
Indicates the genre or type of creative work that serves as the primary source for something (e.g., an adaptation, derivative work, or related resource).
-
B.
designGenre
Indicates that something belongs to, is characterized by, or is created in a particular design style or genre.
-
C.
possibleGenre
Indicates that something may belong to, be classified under, or be associated with a particular genre as one of several potential genre options.
-
D.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
E.
hasGenreOrigin
Indicates that a genre originates from, or has its roots in, a particular source, place, culture, or tradition.
- 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_69f76e414bdc8190996f15a544220a3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.