Triple
T5923868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ML |
E131757
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Scala |
E71988
|
NE 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: Scala | Statement: [ML, influenced, Scala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scala Context triple: [ML, influenced, Scala]
-
A.
Scala
Scala is a historic hilltop town on Italy’s Amalfi Coast, known for its medieval architecture, terraced landscapes, and panoramic views over the surrounding coastline.
-
B.
Scala
chosen
Scala is a high-level, statically typed programming language that unifies object-oriented and functional programming paradigms and runs on the Java Virtual Machine.
-
C.
Scala Center
Scala Center is a non-profit organization at EPFL dedicated to the stewardship, education, and open-source development of the Scala programming language and its ecosystem.
-
D.
Snowpark for Scala
Snowpark for Scala is a developer framework that lets Scala users build and run data pipelines and applications directly in Snowflake using familiar Scala APIs.
-
E.
Kotlin
Kotlin is a modern, statically typed programming language developed by JetBrains that runs on the JVM and is widely used for building Android applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03851189c819094524e8b5080545e |
completed | March 22, 2026, 6:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c0483e3481908e50f8b34b11a878 |
completed | March 23, 2026, 4:23 a.m. |
Created at: March 22, 2026, 4 p.m.