Triple
T18335303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Weider |
E439255
|
entity |
| Predicate | published |
P80
|
FINISHED |
| Object | Shape |
—
|
NE NERFINISHED |
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: Shape | Statement: [Joe Weider, published, Shape]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shape Context triple: [Joe Weider, published, Shape]
-
A.
Shape
chosen
Shape is a health and fitness magazine and digital brand focused on exercise, nutrition, and wellness content, owned by Dotdash Meredith.
-
B.
SHAPE
SHAPE is the central military command headquarters of NATO responsible for planning and executing the alliance’s collective defense operations in Europe.
-
C.
Shape Properties
Shape Properties is a Canadian real estate investment and development company known for owning and redeveloping major shopping centres and mixed-use properties.
-
D.
shape operator
The shape operator is a linear map in differential geometry that describes how a surface curves in different directions by relating changes in its normal vector to directions in the tangent plane.
-
E.
The Shape
The Shape is the silent, masked embodiment of pure evil and the primary antagonist in John Carpenter’s Halloween horror film franchise.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecc91148190aa820fcd466009ce |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.