Triple
T33731674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massimo Vignelli |
E864289
|
entity |
| Predicate | preferredTypefaces |
P42388
|
FINISHED |
| Object | Helvetica |
—
|
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: Helvetica | Statement: [Massimo Vignelli, preferredTypefaces, Helvetica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preferredTypefaces Context triple: [Massimo Vignelli, preferredTypefaces, Helvetica]
-
A.
digitalFontsAvailable
Indicates that digital versions of fonts are available for use or distribution.
-
B.
textTypePreferred
Indicates that one entity has a preferred or favored type or category of text in relation to another entity.
-
C.
typicalFontSupport
Indicates that one entity (such as a system, application, or platform) normally includes or provides support for a particular font or set of fonts under standard conditions.
-
D.
fairType
Indicates the classification or category of a fair (e.g., type of event or exhibition) associated with an entity.
-
E.
hasTypography
chosen
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb1eeb64819083f6f04633b000f2 |
completed | May 3, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:44 a.m.