Triple
T4163190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U3 |
E91577
|
entity |
| Predicate | hasRollingStock |
P1305
|
FINISHED |
| Object |
Siemens DT3
Siemens DT3 is a type of electric multiple unit metro train used on Hamburg’s U-Bahn system.
|
E416701
|
NE FINISHED |
How this triple was built (4 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 DT3 | Statement: [U3, hasRollingStock, Siemens DT3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siemens DT3 Context triple: [U3, hasRollingStock, Siemens DT3]
-
A.
Siemens Avanto
Siemens Avanto is a family of light rail and tram-train vehicles developed by Siemens for urban and regional public transport systems.
-
B.
Siemens SD660
Siemens SD660 is a model of light rail vehicle built by Siemens for use in modern urban transit systems.
-
C.
Siemens Inspiro
Siemens Inspiro is a modern, modular metro train platform developed by Siemens for urban rapid transit systems worldwide.
-
D.
Siemens S70
The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
-
E.
Siemens Combino
Siemens Combino is a low-floor modular tram family widely used in urban public transport systems around the world.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Siemens DT3 Triple: [U3, hasRollingStock, Siemens DT3]
Generated description
Siemens DT3 is a type of electric multiple unit metro train used on Hamburg’s U-Bahn system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Siemens DT3 Target entity description: Siemens DT3 is a type of electric multiple unit metro train used on Hamburg’s U-Bahn system.
-
A.
Siemens Avanto
Siemens Avanto is a family of light rail and tram-train vehicles developed by Siemens for urban and regional public transport systems.
-
B.
Siemens SD660
Siemens SD660 is a model of light rail vehicle built by Siemens for use in modern urban transit systems.
-
C.
Siemens Inspiro
Siemens Inspiro is a modern, modular metro train platform developed by Siemens for urban rapid transit systems worldwide.
-
D.
Siemens S70
The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit systems.
-
E.
Siemens Combino
Siemens Combino is a low-floor modular tram family widely used in urban public transport systems around the world.
- F. None of above. chosen
Provenance (5 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02a9bf348190b99cecd19fe65779 |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f456bf88190b9b8678476ac3803 |
completed | March 14, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_69b57fe89ed0819089d7e56568755b1c |
completed | March 14, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5805cb7e88190b2f6ed6a18de9319 |
completed | March 14, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:44 p.m.