Triple
T15503292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulhouse tramway |
E379014
|
entity |
| Predicate | hasRollingStock |
P1305
|
FINISHED |
| Object | Siemens Avanto |
E354422
|
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: Siemens Avanto | Statement: [Mulhouse tramway, hasRollingStock, Siemens Avanto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siemens Avanto Context triple: [Mulhouse tramway, hasRollingStock, Siemens Avanto]
-
A.
Siemens Avanto
chosen
Siemens Avanto is a family of light rail and tram-train vehicles developed by Siemens for urban and regional public transport systems.
-
B.
Siemens Avenio
Siemens Avenio is a modern low-floor light rail vehicle platform developed by Siemens for urban tram and light rail systems worldwide.
-
C.
Siemens Nexas
Siemens Nexas is a class of electric multiple unit trains used for suburban passenger services on Melbourne’s metropolitan rail network.
-
D.
Siemens Inspiro
Siemens Inspiro is a modern, modular metro train platform developed by Siemens for urban rapid transit systems worldwide.
-
E.
Siemens SD100
The Siemens SD100 is a light rail vehicle model built by Siemens for use on urban trolley and light rail systems such as the San Diego Trolley.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcc5bb88190b8a9a81419a9a38b |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3669f908819087162b1b8a4e4320 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:54 a.m.