Triple
T809879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pixel 8 |
E17519
|
entity |
| Predicate | hasFeature |
P182
|
FINISHED |
| Object | Magic Editor |
E80215
|
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: Magic Editor | Statement: [Pixel 8, hasFeature, Magic Editor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magic Editor Context triple: [Pixel 8, hasFeature, Magic Editor]
-
A.
MagE
MagE is a medium-resolution optical echellette spectrograph used on the Magellan telescopes for detailed spectroscopic studies of astronomical objects.
-
B.
TextEdit
TextEdit is a simple, built-in macOS application for creating and editing plain text and rich text documents.
-
C.
The Mage
The Mage is a powerful and enigmatic magic-user who aids Arthur with supernatural abilities and guidance in the fantasy film "King Arthur: Legend of the Sword."
-
D.
Magic Eraser
chosen
Magic Eraser is a Google Photos tool that uses AI to remove or camouflage unwanted objects and distractions from images.
-
E.
Magic Cauldron
Magic Cauldron is an influential essay by Eric S. Raymond that analyzes and explains the economic models and sustainability of open-source software development.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab26d36c8190800e98890b7ae08e |
completed | March 1, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d8623248190a2306b23ea378534 |
completed | March 3, 2026, 11:23 p.m. |
Created at: March 1, 2026, 7:38 p.m.