Triple
T2440234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siemens S700 |
E53255
|
entity |
| Predicate | family |
P566
|
FINISHED |
| Object | Siemens S70/S700 platform |
E14233
|
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 S70/S700 platform | Statement: [Siemens S700, family, Siemens S70/S700 platform]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siemens S70/S700 platform Context triple: [Siemens S700, family, Siemens S70/S700 platform]
-
A.
Siemens S70
chosen
The Siemens S70 is a modern low-floor light rail vehicle widely used in North American urban transit 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.
Volkswagen Group MQB platform
The Volkswagen Group MQB platform is a modular, transverse-engine vehicle architecture used across numerous VW Group models to streamline production, reduce costs, and share components.
-
E.
Siemens Charger
The Siemens Charger is a family of modern diesel-electric passenger locomotives widely used across North America for intercity and commuter rail services.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f7ba208190810f8ea115110375 |
completed | March 7, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0b3f7188190911f2db0ef2200cc |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:43 p.m.