Triple
T3889685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Israel Hospital |
E88027
|
entity |
| Predicate | trainingPrograms |
P11879
|
FINISHED |
| Object | residency programs |
—
|
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: residency programs | Statement: [Beth Israel Hospital, trainingPrograms, residency programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingPrograms Context triple: [Beth Israel Hospital, trainingPrograms, residency programs]
-
A.
developmentProgramName
Indicates the specific name assigned to a development program associated with an entity or activity.
-
B.
sponsoredPrograms
Indicates that an entity provides financial or resource support to specific programs or initiatives.
-
C.
developmentProgram
Indicates a structured initiative or plan designed to improve, advance, or build the capabilities, resources, or conditions of a target group, system, or area over time.
-
D.
coordinatesProgramsOf
Indicates that one entity organizes and manages the activities or operations of another entity’s programs to ensure they function in a unified and efficient manner.
-
E.
trainingSystem
chosen
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
- 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_69aed9466d548190939f5217a23ed4ac |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecaee7148190ada451ccfc6582ee |
completed | March 9, 2026, 3:52 p.m. |
| PD | Predicate disambiguation | batch_69aee759609c8190985e96ec6d96dedd |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:21 p.m.