Triple
T1812633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 7231 |
E40362
|
entity |
| Predicate | definesHeaderField |
P3703
|
FINISHED |
| Object |
Accept-Language
Accept-Language is an HTTP request header used to indicate the preferred natural languages for the response content.
|
E200846
|
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: Accept-Language | Statement: [RFC 7231, definesHeaderField, Accept-Language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Accept-Language Context triple: [RFC 7231, definesHeaderField, Accept-Language]
-
A.
Region and Language
Region and Language is a Windows Control Panel tool that lets users configure system locale, regional formats, and language settings.
-
B.
Langues
Langues were the regional administrative divisions of the Knights Hospitaller, grouping members by their geographic and linguistic origins.
-
C.
ISO 639
ISO 639 is an international standard that defines codes for the representation of names of languages.
-
D.
Carian language
The Carian language is an extinct Anatolian Indo-European language once spoken in ancient Caria in southwestern Anatolia, known primarily from inscriptions and graffiti.
-
E.
Unicode CLDR
Unicode CLDR is a standardized, collaboratively maintained repository of locale data that underpins internationalization and localization features in software and digital platforms worldwide.
- 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: Accept-Language Triple: [RFC 7231, definesHeaderField, Accept-Language]
Generated description
Accept-Language is an HTTP request header used to indicate the preferred natural languages for the response content.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Accept-Language Target entity description: Accept-Language is an HTTP request header used to indicate the preferred natural languages for the response content.
-
A.
Region and Language
Region and Language is a Windows Control Panel tool that lets users configure system locale, regional formats, and language settings.
-
B.
Langues
Langues were the regional administrative divisions of the Knights Hospitaller, grouping members by their geographic and linguistic origins.
-
C.
ISO 639
ISO 639 is an international standard that defines codes for the representation of names of languages.
-
D.
Carian language
The Carian language is an extinct Anatolian Indo-European language once spoken in ancient Caria in southwestern Anatolia, known primarily from inscriptions and graffiti.
-
E.
Unicode CLDR
Unicode CLDR is a standardized, collaboratively maintained repository of locale data that underpins internationalization and localization features in software and digital platforms worldwide.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0003d308190a024f8c03c5f5dad |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5e5142c8190bc90da38b02e95e2 |
completed | March 8, 2026, 5:46 p.m. |
| NEDg | Description generation | batch_69adb69d10188190b78bece656249ecd |
completed | March 8, 2026, 5:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb8c122e881908f0640edc5aaf305 |
completed | March 8, 2026, 5:58 p.m. |
Created at: March 4, 2026, 7:32 p.m.