Triple
T3419157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Google I/O 2014 |
E72076
|
entity |
| Predicate | announced |
P429
|
FINISHED |
| Object | Google Cloud Dataflow |
E97117
|
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: Google Cloud Dataflow | Statement: [Google I/O 2014, announced, Google Cloud Dataflow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Google Cloud Dataflow Context triple: [Google I/O 2014, announced, Google Cloud Dataflow]
-
A.
Google Cloud Dataflow
chosen
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
B.
Google Cloud Dataproc
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
C.
Google Cloud
Google Cloud is Alphabet Inc.'s cloud computing platform offering infrastructure, platform, and software services for building, deploying, and scaling applications and data solutions.
-
D.
Azure Data Factory
Azure Data Factory is a cloud-based data integration service from Microsoft that enables users to create, schedule, and orchestrate data pipelines for moving and transforming data at scale across diverse sources.
-
E.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb94d6808819080997df30119e71e |
completed | March 8, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b354701e908190a8a7f14ae578fa5d |
completed | March 13, 2026, 12:04 a.m. |
Created at: March 8, 2026, 3:15 p.m.