Triple
T7291845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Redding Municipal Airport |
E164415
|
entity |
| Predicate | FAAcode |
P420
|
FINISHED |
| Object | RDD |
E654295
|
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: RDD | Statement: [Redding Municipal Airport, FAAcode, RDD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RDD Context triple: [Redding Municipal Airport, FAAcode, RDD]
-
A.
RDD
chosen
RDD is the three-letter IATA airport code for Redding Municipal Airport in Redding, California.
-
B.
Spark
"Spark" is a virtuosic jazz fusion composition by Japanese pianist Hiromi Uehara, showcasing her signature blend of technical brilliance and energetic, genre-blurring style.
-
C.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
-
D.
MapReduce
MapReduce is a programming model and processing framework for distributed computation of large data sets across clusters of computers.
-
E.
Dask
Dask is an open-source parallel computing library for Python that enables scalable, distributed data processing and analytics using familiar interfaces like NumPy, pandas, and scikit-learn.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb6e8f3881908628b3d41aad70c6 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e53ab41c8190b081e90fa6a1145c |
completed | March 28, 2026, 2:27 p.m. |
Created at: March 27, 2026, 3 p.m.