Triple
T28272412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butterfly Effect |
E712891
|
entity |
| Predicate | featuresAutoTune |
P196817
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Butterfly Effect, featuresAutoTune, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresAutoTune Context triple: [Butterfly Effect, featuresAutoTune, yes]
-
A.
featuresAutomaton
Indicates that one entity includes, incorporates, or makes use of an automaton as a functional component or characteristic.
-
B.
featuresMechanic
Indicates that something includes or incorporates a particular mechanic as part of its design or functionality.
-
C.
controlFeatures
Indicates that one entity has the ability to configure, manage, or influence the operational settings or characteristics of another entity.
-
D.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
E.
featuresModel
Indicates that one entity includes, exposes, or is characterized by a particular model as one of its defining components or capabilities.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
| PDg | Predicate description generation | batch_69fe6b7a823881909dc2037fe25bea24 |
completed | May 8, 2026, 11:02 p.m. |
Created at: April 27, 2026, 11:18 p.m.