Triple
T9004605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple ProRAW |
E215112
|
entity |
| Predicate | containerFormat |
P31899
|
FINISHED |
| Object | DNG |
E163317
|
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: DNG | Statement: [Apple ProRAW, containerFormat, DNG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DNG Context triple: [Apple ProRAW, containerFormat, DNG]
-
A.
DNG
chosen
DNG (Digital Negative) is an open, publicly documented raw image file format developed by Adobe for long-term archival and broad compatibility of digital photographs.
-
B.
NEF
NEF (Network Exposure Function) is a 5G core network function that securely exposes network services and capabilities to external applications and third-party systems via standardized APIs.
-
C.
Tiff
Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
-
D.
DN
DN is the official vehicle registration code used for the Indian union territory of Dadra and Nagar Haveli and Daman and Diu.
-
E.
DN
DN is a UK postcode area covering Doncaster and surrounding parts of South Yorkshire and Lincolnshire, including North East Lincolnshire.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6959497c8190a748c78504dd2eb6 |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e3f0c88190ae688632be25e5c9 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.