Triple
T9456338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | oersted |
E228023
|
entity |
| Predicate | unitSystem |
P29841
|
FINISHED |
| Object | CGS-EMU |
E621092
|
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: CGS-EMU | Statement: [oersted, unitSystem, CGS-EMU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CGS-EMU Context triple: [oersted, unitSystem, CGS-EMU]
-
A.
CGS-EMU system
chosen
The CGS-EMU system is a variant of the centimeter–gram–second (CGS) system of units that uses the electromagnetic (EMU) subsystem for electrical and magnetic quantities, including the gauss as a unit of magnetic flux density.
-
B.
Comeng EMU
The Comeng EMU is a long-serving class of electric multiple unit trains used on Melbourne's suburban rail network.
-
C.
Civia EMU
Civia EMU is a class of electric multiple unit commuter trains used by Spain’s Renfe for suburban and regional passenger services.
-
D.
Siemens-Duewag U2
The Siemens-Duewag U2 is a high-floor light rail vehicle widely used in North American transit systems, notably in early expansions of Calgary’s CTrain network.
-
E.
Z 5600 EMU
The Z 5600 EMU is a class of French electric multiple unit trains built for suburban commuter services around Paris, notably operating on the RER network.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f8f7e1481909318e473ab4d6460 |
completed | April 1, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122849fec81908a8e7363d6bab4ed |
completed | April 4, 2026, 2:39 p.m. |
Created at: March 30, 2026, 7:52 p.m.