Triple
T5176640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tvärbanan |
E116814
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | Line L31 |
E500445
|
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: Line L31 | Statement: [Tvärbanan, hasLine, Line L31]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line L31 Context triple: [Tvärbanan, hasLine, Line L31]
-
A.
Line L30
chosen
Line L30 is a light rail route of Stockholm’s Tvärbanan system that serves as one of the cross-city tram lines connecting suburbs around the Swedish capital.
-
B.
Line 31
Line 31 is a planned rapid transit line of the Shenzhen Metro system in Shenzhen, China.
-
C.
Line 29
Line 29 is a planned rapid transit line of the Shenzhen Metro system in Shenzhen, China.
-
D.
Line 34
Line 34 is a planned rapid transit line in the Shenzhen Metro system in Shenzhen, China.
-
E.
Line 33
Line 33 is a planned rapid transit line of the Shenzhen Metro system in Shenzhen, China.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7974a5308190819b100e07189131 |
completed | March 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee07a6620819089e2b3fcb322a47e |
completed | March 21, 2026, 6:16 p.m. |
Created at: March 20, 2026, 1:45 p.m.