Triple
T32122805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSFastEnumeration |
E820424
|
entity |
| Predicate | languageFeatureType |
P200989
|
FINISHED |
| Object | runtime protocol |
—
|
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: runtime protocol | Statement: [NSFastEnumeration, languageFeatureType, runtime protocol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageFeatureType Context triple: [NSFastEnumeration, languageFeatureType, runtime protocol]
-
A.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
B.
languageTypeCovered
Indicates that one entity provides coverage, support, or applicability for a particular type or category of language associated with another entity.
-
C.
languageCore
Indicates a fundamental or primary language associated with or used by an entity.
-
D.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
E.
usedInLanguageFeature
Indicates that something (such as a construct, pattern, or element) is employed as a feature within a particular language.
- 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_69f34902d42c819083a8e6bba9a8bb9a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ffc083a54c8190ac80d05ee8d20a6b |
completed | May 9, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69ffbfeb05b88190b4d50ce8124004d9 |
completed | May 9, 2026, 11:14 p.m. |
| PDg | Predicate description generation | batch_69ffc082a4e881908a92313d2c755afe |
completed | May 9, 2026, 11:17 p.m. |
Created at: May 1, 2026, 12:28 a.m.