Triple
T10763766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Structural Pattern Matching |
E253899
|
entity |
| Predicate | usesKeyword |
P67723
|
FINISHED |
| Object | case _ as wildcard pattern |
—
|
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: case _ as wildcard pattern | Statement: [Structural Pattern Matching, usesKeyword, case _ as wildcard pattern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesKeyword Context triple: [Structural Pattern Matching, usesKeyword, case _ as wildcard pattern]
-
A.
associatedKeyword
Indicates that one entity is linked to or characterized by a particular keyword used for identification, categorization, or retrieval.
-
B.
usesWord
chosen
Indicates that one entity employs, contains, or makes use of a particular word in its expression, content, or communication.
-
C.
usedTerm
Indicates that one entity employed, referenced, or applied a particular term in some context.
-
D.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a504948190943f0e27c0d891ed |
completed | April 9, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.