Triple
T4118880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernst Mach |
E90361
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mach |
E90361
|
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: Mach | Statement: [Ernst Mach, familyName, Mach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mach Context triple: [Ernst Mach, familyName, Mach]
-
A.
Mach
chosen
Mach is a surname most famously associated with Austrian physicist and philosopher Ernst Mach, whose work on the physics of motion and critical views on Newtonian mechanics influenced both science and philosophy.
-
B.
Mach
Mach is a pioneering microkernel-based operating system kernel architecture that introduced advanced concepts like message passing and modularity, influencing many modern OS designs.
-
C.
Mach 1
Mach 1 is a performance-oriented version of the Ford Mustang known for its enhanced power, handling, and distinctive styling cues.
-
D.
Blisk
Blisk is a fictional setting or universe in which the character or concept known as Blink appears or is utilized.
-
E.
Thar
Thar is a city located in Saudi Arabia’s Najran Region, near the country’s southern border.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01f48c1c8190aacde6cdf70d7775 |
completed | March 9, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576abe02081908a1b0322758089bd |
completed | March 14, 2026, 2:54 p.m. |
Created at: March 9, 2026, 3:41 p.m.