Triple
T17047024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Yeargan |
E413595
|
entity |
| Predicate | hasCreatedSceneryFor |
P125641
|
FINISHED |
| Object | Broadway musicals |
—
|
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: Broadway musicals | Statement: [Michael Yeargan, hasCreatedSceneryFor, Broadway musicals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCreatedSceneryFor Context triple: [Michael Yeargan, hasCreatedSceneryFor, Broadway musicals]
-
A.
hasScenicResource
Indicates that an entity possesses or is associated with a natural or visual feature valued for its aesthetic or scenic qualities.
-
B.
hasTerrainFor
Indicates that a location or area possesses terrain suitable or designated for a particular use, activity, or feature.
-
C.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
D.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
-
E.
hasScenicAccessTo
Indicates that one place or object provides a visually appealing or notable view of another place or object.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3da9e3d8881909f197aba0e4c97e7 |
completed | April 18, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.