Triple
T575833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blink |
E13758
|
entity |
| Predicate | renderingModel |
P15683
|
FINISHED |
| Object | multi-process architecture (via Chromium) |
—
|
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: multi-process architecture (via Chromium) | Statement: [Blink, renderingModel, multi-process architecture (via Chromium)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: renderingModel Context triple: [Blink, renderingModel, multi-process architecture (via Chromium)]
-
A.
renderedBy
Indicates that something is produced, drawn, or visually generated by a particular agent, tool, or process.
-
B.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
C.
notableRendering
Indicates that one entity is a significant or well-known visual or artistic depiction of another entity.
-
D.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
E.
publishingModel
Indicates the method or framework by which content is produced, distributed, and made publicly available.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b67395c8190a8046ff7debe9d1f |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c692288190b88f30299516b5ba |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985a2d08819090947895d9439e06 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.