Triple
T24433620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mannes College of Music |
E616064
|
entity |
| Predicate | offersEnsemble |
P156120
|
FINISHED |
| Object | orchestra |
—
|
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: orchestra | Statement: [Mannes College of Music, offersEnsemble, orchestra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersEnsemble Context triple: [Mannes College of Music, offersEnsemble, orchestra]
-
A.
offersEdition
Indicates that one entity provides or makes available a particular version or edition of another entity.
-
B.
offersObject
Indicates that a subject provides or makes available a specific object to another party as an offer.
-
C.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
D.
offersInterface
Indicates that one entity provides or exposes a specific interface that another entity can use or interact with.
-
E.
offersViewOf
Indicates that one entity provides a vantage point from which another entity can be seen or visually appreciated.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2978469a081909f17b6955809bbef |
completed | April 29, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:16 a.m.