Triple
T2703272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 2068 |
E59281
|
entity |
| Predicate | definesHeaderField |
P3703
|
FINISHED |
| Object | Accept-Language |
E200846
|
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: Accept-Language | Statement: [RFC 2068, definesHeaderField, Accept-Language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Accept-Language Context triple: [RFC 2068, definesHeaderField, Accept-Language]
-
A.
Accept-Language
chosen
Accept-Language is an HTTP request header used to indicate the preferred natural languages for the response content.
-
B.
Content-Language
Content-Language is an HTTP header field that indicates the natural language(s) intended for the audience of the enclosed content.
-
C.
Region and Language
Region and Language is a Windows Control Panel tool that lets users configure system locale, regional formats, and language settings.
-
D.
SSH Language Tags
SSH Language Tags are standardized identifiers used within the SSH protocol to specify human languages for messages and data, enabling proper localization and internationalization.
-
E.
Accept-Encoding
Accept-Encoding is an HTTP request header that tells the server which content-encoding algorithms (like gzip or deflate) the client can handle so the server can choose an appropriate compression method.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda5011bc8190ae4e41da391e759c |
completed | March 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf76caec8190930ead7931f7ea91 |
completed | March 10, 2026, 5:43 a.m. |
Created at: March 6, 2026, 9:55 p.m.