Triple
T6525375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Instruments |
E151288
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | NI |
E602860
|
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: NI | Statement: [National Instruments, brand, NI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NI Context triple: [National Instruments, brand, NI]
-
A.
NI
NI is the vehicle registration code used on license plates for the German federal state of Lower Saxony.
-
B.
NI
NI is the vehicle registration code used on license plates for the Serbian city of Niš.
-
C.
NI
chosen
NI (National Instruments) is an American technology company known for its automated test and measurement hardware and software platforms used by engineers and scientists worldwide.
-
D.
NI
NI is the abbreviation for Nuevas Ideas, a political party in El Salvador founded by President Nayib Bukele.
-
E.
NU
NU is a leading Japanese national research university located in Nagoya, known for its strong programs in science, engineering, and the humanities.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ada77b448190b6e0e07494fb4dd3 |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eece13088190a49a72d5a784f6f8 |
completed | March 27, 2026, 8:55 p.m. |
Created at: March 27, 2026, 1:45 p.m.