Triple
T4384500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahrain Grand Prix |
E99207
|
entity |
| Predicate | medicalCar |
P56270
|
FINISHED |
| Object | Aston Martin or Mercedes medical car (various seasons) |
—
|
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: Aston Martin or Mercedes medical car (various seasons) | Statement: [Bahrain Grand Prix, medicalCar, Aston Martin or Mercedes medical car (various seasons)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalCar Context triple: [Bahrain Grand Prix, medicalCar, Aston Martin or Mercedes medical car (various seasons)]
-
A.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
B.
focusesOnMedicalCare
Indicates that one entity directs attention, resources, or activity specifically toward providing or improving medical care for another entity.
-
C.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
D.
healthSystem
Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
-
E.
hospitalFunction
Indicates the specific medical or administrative role, service, or operational purpose that a hospital performs.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35263970c8190904ee20d81715833 |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:19 p.m.