Triple
T29863902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mod_brotli |
E758395
|
entity |
| Predicate | supportsContentEncodingHeader |
P67298
|
FINISHED |
| Object | br |
—
|
LITERAL 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: br | Statement: [mod_brotli, supportsContentEncodingHeader, br]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsContentEncodingHeader Context triple: [mod_brotli, supportsContentEncodingHeader, br]
-
A.
differenceFromContentEncoding
Indicates that one encoding or representation of content differs from another specified content encoding.
-
B.
usesEncodingRules
Indicates that one entity applies or conforms to a specified set of encoding rules when representing or transforming information.
-
C.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
D.
supportsCompressedFiles
chosen
Indicates that one entity is capable of handling, reading, or working with files that are stored in a compressed format.
-
E.
hasMessageContent
Indicates that an entity (such as a message or communication) contains or is associated with specific textual or data content.
- F. None of above.
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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 5:50 p.m.