Triple
T10763749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Structural Pattern Matching |
E253899
|
entity |
| Predicate | hasSyntaxKeyword |
P95858
|
FINISHED |
| Object | match |
—
|
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: match | Statement: [Structural Pattern Matching, hasSyntaxKeyword, match]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSyntaxKeyword Context triple: [Structural Pattern Matching, hasSyntaxKeyword, match]
-
A.
definesSyntax
Indicates that one entity specifies or determines the formal structure, rules, or grammar by which another entity is expressed or interpreted.
-
B.
hasBCPKeyword
Indicates that an entity is associated with, labeled by, or contains a specific BCP (Business Continuity Plan) keyword.
-
C.
hasMacroLanguage
Indicates that one language functions as a macrolanguage encompassing or grouping together multiple closely related individual languages or varieties.
-
D.
hasKnownGrammar
Indicates that an entity is associated with a grammar whose structure and rules are already defined or understood.
-
E.
hasDirective
Indicates that one entity issues, contains, or is governed by a specific directive or instruction associated with another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:16 p.m.