Triple
T816377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NumPy |
E17659
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | JAX |
E95194
|
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: JAX | Statement: [NumPy, influenced, JAX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JAX Context triple: [NumPy, influenced, JAX]
-
A.
JAX
chosen
JAX is a high-performance numerical computing library for Python that combines NumPy-like APIs with automatic differentiation and just-in-time compilation, widely used for machine learning and scientific computing.
-
B.
JAXPORT
JAXPORT is the public seaport authority for Jacksonville, Florida, serving as a major U.S. hub for container, automobile, and bulk cargo shipping.
-
C.
IJ Bay
IJ Bay is a body of water in the Netherlands that forms a key waterfront and harbor area for the city of Amsterdam.
-
D.
Dix
Dix is the surname of Dorothea Dix, the 19th-century American social reformer known for her pioneering work in mental health care and prison reform.
-
E.
Savannah
Savannah is a historic coastal city in the U.S. state of Georgia, renowned for its well-preserved architecture, cobblestone squares, and rich Southern cultural heritage.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab621d2c819083f10bff4f66c482 |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d8d1a448190be8494fa2776615a |
completed | March 3, 2026, 11:23 p.m. |
Created at: March 1, 2026, 7:38 p.m.