Triple
T10214215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Core Animation |
E242401
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Quartz Core |
E229050
|
NE 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: Quartz Core | Statement: [Core Animation, partOf, Quartz Core]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quartz Core Context triple: [Core Animation, partOf, Quartz Core]
-
A.
Quartz at Work
Quartz at Work is a business-focused publication from Quartz that offers analysis, insights, and commentary on the modern workplace, management, and careers.
-
B.
Quartz
Quartz is a digital news outlet known for its global business journalism, data-driven reporting, and mobile-first storytelling.
-
C.
Quartz
chosen
Quartz is Apple's 2D graphics rendering and compositing engine that underpins the visual display system in macOS.
-
D.
Quartz Media
Quartz Media is a global digital news organization known for its data-driven coverage of business, technology, and geopolitics, including region-focused platforms like Quartz Africa.
-
E.
Quart
Quart is a Python web microframework with an asyncio-based design that provides an ASGI-compatible, Flask-like API for building asynchronous web applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa273bdc8190bc4cf67a7923cebc |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652ea80dc81908bc65ee2ec390467 |
completed | April 8, 2026, 1:06 p.m. |
Created at: April 6, 2026, 11:04 a.m.