Triple
T14342900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | java.nio |
E355645
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | java.nio.DoubleBuffer |
E355645
|
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: java.nio.DoubleBuffer | Statement: [java.nio, contains, java.nio.DoubleBuffer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: java.nio.DoubleBuffer Context triple: [java.nio, contains, java.nio.DoubleBuffer]
-
A.
java.nio
chosen
java.nio is a Java API package that provides non-blocking I/O, buffer management, and scalable channel-based input/output operations.
-
B.
NIO
NIO is a Chinese electric vehicle manufacturer known for its premium smart EVs and innovative battery-swapping technology.
-
C.
DBL
DBL is the vehicle registration code assigned to motor vehicles registered in Bolesławiec, a town in southwestern Poland.
-
D.
DBL
DBL is a doctoral-level business leadership program focused on advanced management and leadership studies.
-
E.
Verdouble
Verdouble is a river in southern France that flows through the Pyrénées-Orientales and Aude departments, known for its scenic gorges and Mediterranean landscapes.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e87febc8190a63c668cbd0fd713 |
completed | April 14, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd469d899081909103563f209dd944 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:14 a.m.