Triple
T10574967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodalies de Catalunya |
E249583
|
entity |
| Predicate | hasService |
P182
|
FINISHED |
| Object |
R35
R35 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
|
E875885
|
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: R35 | Statement: [Rodalies de Catalunya, hasService, R35]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R35 Context triple: [Rodalies de Catalunya, hasService, R35]
-
A.
R33
R33 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
-
B.
R38
R38 is a regional commuter rail line in Catalonia that forms part of the Rodalies de Catalunya network.
-
C.
R36
R36 is a regional commuter rail line within the Rodalies de Catalunya network serving passengers in Catalonia, Spain.
-
D.
R36
R36 is a regional road in South Africa that connects the town of Lydenburg with other major routes and settlements in the region.
-
E.
Nissan 350Z
The Nissan 350Z is a two-seat sports car from Nissan’s Z-car line, known for its V6 power, rear-wheel drive, and popularity among driving enthusiasts and tuners in the 2000s.
- 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: R35 Triple: [Rodalies de Catalunya, hasService, R35]
Generated description
R35 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: R35 Target entity description: R35 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
-
A.
R33
R33 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
-
B.
R38
R38 is a regional commuter rail line in Catalonia that forms part of the Rodalies de Catalunya network.
-
C.
R36
R36 is a regional commuter rail line within the Rodalies de Catalunya network serving passengers in Catalonia, Spain.
-
D.
R36
R36 is a regional road in South Africa that connects the town of Lydenburg with other major routes and settlements in the region.
-
E.
Nissan 350Z
The Nissan 350Z is a two-seat sports car from Nissan’s Z-car line, known for its V6 power, rear-wheel drive, and popularity among driving enthusiasts and tuners in the 2000s.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52749dda08190b0c9627a931c5848 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b5025b88190a078f5ad7b9cb3d5 |
completed | April 10, 2026, 9:27 p.m. |
| NEDg | Description generation | batch_69d96dee84f48190bf5b0cb1115a8bba |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9708824208190acf75933962d690f |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 6, 2026, 12:38 p.m.