Triple
T4554718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crowdsignal |
E120452
|
entity |
| Predicate | supportsQuestionType |
P24486
|
FINISHED |
| Object | multiple choice |
—
|
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: multiple choice | Statement: [Crowdsignal, supportsQuestionType, multiple choice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsQuestionType Context triple: [Crowdsignal, supportsQuestionType, multiple choice]
-
A.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
B.
typeOfSupport
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
C.
supportsProgramType
Indicates that one entity is capable of handling, offering, or being compatible with a specified type of program.
-
D.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
E.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd58127ed08190a04962a43afb888b |
completed | March 20, 2026, 2:22 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.