Triple
T17517432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PlatformIO |
E426601
|
entity |
| Predicate | supportsIntegration |
P203
|
FINISHED |
| Object | Travis CI |
—
|
NE NERFINISHED |
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: Travis CI | Statement: [PlatformIO, supportsIntegration, Travis CI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Travis CI Context triple: [PlatformIO, supportsIntegration, Travis CI]
-
A.
Travis CI
chosen
Travis CI is a hosted continuous integration service widely used to automatically build and test software projects, especially those hosted on GitHub.
-
B.
CircleCI
CircleCI is a cloud-based continuous integration and delivery platform that automates building, testing, and deploying software.
-
C.
TeamCity
TeamCity is a commercial continuous integration and build management server developed by JetBrains, used to automate building, testing, and deploying software projects.
-
D.
Jenkins
Jenkins is a common English-language surname borne by numerous notable individuals across sports, politics, arts, and other fields.
-
E.
Jenkins
Jenkins is a fictional character who serves as the main protagonist in the story "City."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452615a8481909974e9855ea7a8e4 |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:49 a.m.