Triple
T271496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MAX Yellow Line |
E5642
|
entity |
| Predicate | hasRollingStockType |
P1305
|
FINISHED |
| Object | Siemens S70 |
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 | Statement: [MAX Yellow Line, hasRollingStockType, Siemens S70]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siemens S70 Context triple: [MAX Yellow Line, hasRollingStockType, Siemens S70]
-
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.
Erla Maschinenwerk
Erla Maschinenwerk was a German aircraft manufacturing company best known for producing Messerschmitt fighter planes under license during World War II.
-
D.
Rockwell
Rockwell is an American singer and songwriter best known for his 1984 hit single "Somebody's Watching Me."
-
E.
Philips Wing
Philips Wing is a modern exhibition and gallery space within Amsterdam’s Rijksmuseum, often used for temporary and special exhibitions.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3914eba9081908cdef8b719c9b20b |
completed | March 1, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.