Triple
T25533995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IFTTT |
E639995
|
entity |
| Predicate | usesTerminology |
P137294
|
FINISHED |
| Object | applets |
—
|
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: applets | Statement: [IFTTT, usesTerminology, applets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTerminology Context triple: [IFTTT, usesTerminology, applets]
-
A.
usesTerminologyFrom
Indicates that one entity adopts or incorporates the specialized terms or vocabulary originating from another entity or source.
-
B.
useOfTerm
chosen
Indicates that one entity employs or applies a specific term or expression in reference to another entity or context.
-
C.
officialTerminology
Indicates that the associated term is the formally recognized or standard expression used in an official or authoritative context for a given concept or entity.
-
D.
terminologyNote
Indicates that there is an explanatory note or comment clarifying the use, meaning, or nuances of a specific term in the relationship.
-
E.
usesControlledVocabulary
Indicates that one entity selects terms or values from a predefined, standardized set rather than using free-form or arbitrary expressions.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8652c908190bee57d3f2663e6b2 |
completed | May 2, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 3:16 p.m.