Triple
T7027042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Auburn Hospital |
E162973
|
entity |
| Predicate | hasCancerCenter |
P10262
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mount Auburn Hospital, hasCancerCenter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCancerCenter Context triple: [Mount Auburn Hospital, hasCancerCenter, yes]
-
A.
isClinicalCenter
Indicates that an entity functions as a clinical center, typically serving as a site for clinical activities such as patient care, clinical trials, or medical research.
-
B.
hasMedicalCenter
chosen
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
C.
hasResearchHospital
Indicates that an entity possesses, is associated with, or operates a hospital facility dedicated to conducting medical or clinical research.
-
D.
designatedAsFlagshipHospitalFor
Indicates that one hospital has been officially selected or recognized as the primary or leading flagship institution for another entity (such as a health system, region, or organization).
-
E.
isPartOfAcademicMedicalCenter
Indicates that an entity belongs to, is affiliated with, or operates as a component of a larger academic medical center.
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:35 p.m.