Triple
T28249530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MQDs |
E712275
|
entity |
| Predicate | statusYearType |
P7173
|
FINISHED |
| Object | Medallion Year |
—
|
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: Medallion Year | Statement: [MQDs, statusYearType, Medallion Year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusYearType Context triple: [MQDs, statusYearType, Medallion Year]
-
A.
hasYearType
Indicates a relationship where an entity is associated with a specific classification or category of year (such as calendar, fiscal, academic, or other year type).
-
B.
type1Years
Indicates the number of years associated with being in or under a specified "type1" classification or status.
-
C.
yearType
chosen
Indicates the classification or category assigned to a specific year (e.g., academic, fiscal, calendar, leap).
-
D.
hasTypeOfYear
Indicates that a given year is classified as belonging to a specific type or category of year (e.g., fiscal, academic, leap).
-
E.
GIStatusYear
Indicates the gastrointestinal health or diagnostic status associated with a specific calendar year.
- 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
Created at: April 27, 2026, 11:03 p.m.