Triple
T18705292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TensorFlow Model Analysis |
E457352
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | TFMA |
—
|
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: TFMA | Statement: [TensorFlow Model Analysis, abbreviation, TFMA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TFMA Context triple: [TensorFlow Model Analysis, abbreviation, TFMA]
-
A.
TensorFlow Model Analysis
chosen
TensorFlow Model Analysis is an open-source library for evaluating, validating, and monitoring machine learning models—especially at scale and on large datasets—within TensorFlow-based pipelines.
-
B.
TensorFlow Transform
TensorFlow Transform is a TensorFlow-based library for performing scalable, full-pass data preprocessing and feature engineering that can be applied consistently in both training and serving.
-
C.
TF
TF is the abbreviation for the Faculty of Engineering at the University of Freiburg, a German institution focused on engineering and technology education and research.
-
D.
TF
TF is the vehicle registration code used for motor vehicles registered in the Spanish province of Santa Cruz de Tenerife in the Canary Islands.
-
E.
TF
TF is the French abbreviation for the Federal Supreme Court of Switzerland, the country’s highest judicial authority.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671665bc8190b9b4a4ce4ec5b2eb |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:49 a.m.