Triple
T28229443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Ledwidge |
E711683
|
entity |
| Predicate | hasBestsellingStatus |
P51791
|
FINISHED |
| Object | New York Times bestselling author |
—
|
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: New York Times bestselling author | Statement: [Michael Ledwidge, hasBestsellingStatus, New York Times bestselling author]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBestsellingStatus Context triple: [Michael Ledwidge, hasBestsellingStatus, New York Times bestselling author]
-
A.
bestsellingStatus
chosen
Indicates that an item has achieved a high sales ranking or volume, typically qualifying it as a “bestseller” within a defined market or category.
-
B.
timeInNewYorkTimesBestSellerList
Indicates the duration or specific time period that an item spent on The New York Times Best Seller list.
-
C.
isPopularAt
Indicates that an entity enjoys a high level of recognition, approval, or favor within a specified place, context, or time.
-
D.
isBestSellingCookieBrand
Indicates that a cookie brand holds the highest sales or market share compared to other cookie brands within a defined market or time period.
-
E.
isOneOfBestSellingCars
Indicates that the car is among the top-selling cars within a specified market or time period.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 10:51 p.m.