Triple
T35987721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weill Cornell Medicine-Qatar |
E1040756
|
entity |
| Predicate | grantsSameDegreeAs |
P189369
|
FINISHED |
| Object | Weill Cornell Medicine in New York |
—
|
NE NERFINISHED |
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: Weill Cornell Medicine in New York | Statement: [Weill Cornell Medicine-Qatar, grantsSameDegreeAs, Weill Cornell Medicine in New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantsSameDegreeAs Context triple: [Weill Cornell Medicine-Qatar, grantsSameDegreeAs, Weill Cornell Medicine in New York]
-
A.
grantsDegreeIn
Indicates that an institution or authority confers an academic degree in a specified field or discipline.
-
B.
grantedDegreesTo
Indicates that one entity has officially conferred academic degrees upon another entity.
-
C.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
-
D.
grantsDegreeThrough
Indicates that an institution confers a degree to an individual by means of a specified program, process, or pathway.
-
E.
hasDegreeIn
Indicates that an entity possesses an academic degree in a specified field or discipline.
- 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_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbbc48b75c8190bec27dd4b7de797f |
completed | May 6, 2026, 10:10 p.m. |
Created at: May 3, 2026, 4:07 p.m.