Triple
T6519566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SRU |
E148346
|
entity |
| Predicate | requestEncoding |
P71373
|
FINISHED |
| Object | URL query parameters |
—
|
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: URL query parameters | Statement: [SRU, requestEncoding, URL query parameters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requestEncoding Context triple: [SRU, requestEncoding, URL query parameters]
-
A.
requestContent
Indicates that one entity asks another entity to provide specific information, data, or material.
-
B.
dataEncodingMethod
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
-
C.
textEncoderType
Indicates the specific kind or configuration of encoder used to process or represent text in a system or model.
-
D.
encodedIn
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
E.
encodingForm
Indicates the specific format or scheme used to encode information or data in a representation or communication.
- F. None of above. chosen
Provenance (4 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_69c687e68e748190baceb9298f32d3ed |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ac11d0e481908103c4b51de9521e |
completed | March 27, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69c68abbc7148190a8270d47fe10cc31 |
completed | March 27, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69c69f362ee4819090e8fa48caef7d7d |
completed | March 27, 2026, 3:16 p.m. |
Created at: March 27, 2026, 1:45 p.m.