Triple
T1936406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liquid Retina XDR |
E41452
|
entity |
| Predicate | feature |
P374
|
FINISHED |
| Object |
True Tone
True Tone is an Apple display technology that automatically adjusts a screen’s color temperature and brightness to match ambient lighting for a more natural viewing experience.
|
E216045
|
NE FINISHED |
How this triple was built (4 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: True Tone | Statement: [Liquid Retina XDR, feature, True Tone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: True Tone Context triple: [Liquid Retina XDR, feature, True Tone]
-
A.
Real Tone
Real Tone is Google's camera technology designed to more accurately and beautifully render diverse skin tones in photos and videos.
-
B.
Touchstone
Touchstone is a publishing imprint known for releasing a wide range of commercial fiction and nonfiction titles.
-
C.
Luce
Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
-
D.
Sparkle
Sparkle is a Georgia-Pacific paper towel brand known for its affordable, everyday household cleaning products.
-
E.
Whisper
Whisper is an open-source automatic speech recognition system by OpenAI that transcribes and translates spoken language with high accuracy across many languages.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: True Tone Triple: [Liquid Retina XDR, feature, True Tone]
Generated description
True Tone is an Apple display technology that automatically adjusts a screen’s color temperature and brightness to match ambient lighting for a more natural viewing experience.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: True Tone Target entity description: True Tone is an Apple display technology that automatically adjusts a screen’s color temperature and brightness to match ambient lighting for a more natural viewing experience.
-
A.
Real Tone
Real Tone is Google's camera technology designed to more accurately and beautifully render diverse skin tones in photos and videos.
-
B.
Touchstone
Touchstone is a publishing imprint known for releasing a wide range of commercial fiction and nonfiction titles.
-
C.
Luce
Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
-
D.
Sparkle
Sparkle is a Georgia-Pacific paper towel brand known for its affordable, everyday household cleaning products.
-
E.
Whisper
Whisper is an open-source automatic speech recognition system by OpenAI that transcribes and translates spoken language with high accuracy across many languages.
- F. None of above. chosen
Provenance (5 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2c5f6e481909b2d95861e2098f9 |
completed | March 7, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3f6285c8190925af156f49cf9a2 |
completed | March 8, 2026, 10:11 p.m. |
| NEDg | Description generation | batch_69adf4aea46481908b5da7c4251dd867 |
completed | March 8, 2026, 10:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf52b63c481908fcb9db4c40875b4 |
completed | March 8, 2026, 10:16 p.m. |
Created at: March 4, 2026, 7:35 p.m.