Triple
T12251083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orléans tramway |
E291971
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line A
Line A is a principal route of the Orléans tramway system in France, providing urban light rail transit across key areas of the city.
|
E972085
|
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: Line A | Statement: [Orléans tramway, hasLine, Line A]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line A Context triple: [Orléans tramway, hasLine, Line A]
-
A.
Line A
Line A is a line of the Mexico City Metro system that serves the eastern part of the metropolitan area, connecting central Mexico City with several suburban municipalities.
-
B.
Line A
Line A is the main north–south rapid transit line of the Medellín Metro system in Colombia, serving as its busiest and most central corridor.
-
C.
Line A
Line A is the primary route of the Bilbao tram system, serving key areas of the city with modern light rail service.
-
D.
Line A
Line A is one of the main lines of the Prague Metro, running east–west through the city and serving several central and residential districts.
-
E.
Line A
Line A is one of the main tram lines serving the city of Reims, France, providing urban public transportation across key districts.
- 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: Line A Triple: [Orléans tramway, hasLine, Line A]
Generated description
Line A is a principal route of the Orléans tramway system in France, providing urban light rail transit across key areas of the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line A Target entity description: Line A is a principal route of the Orléans tramway system in France, providing urban light rail transit across key areas of the city.
-
A.
Line A
Line A is one of the main tram lines serving the city of Reims, France, providing urban public transportation across key districts.
-
B.
Line A
Line A is one of the main routes of the Strasbourg tramway network, providing key light-rail transit across the city.
-
C.
Line A
Line A is the primary route of the Bilbao tram system, serving key areas of the city with modern light rail service.
-
D.
Line A
Line A is one of the main lines of the Prague Metro, running east–west through the city and serving several central and residential districts.
-
E.
Line A
Line A is the historic first subway line of the Buenos Aires Underground, known for its early 20th-century wooden cars and route through central neighborhoods.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cc6983c81909bf479d15879a357 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60abbf75c81908a25e1c0a4aee8c1 |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60f2154c8819081f9cf6f51e5255b |
completed | May 2, 2026, 2:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60fe8c2ec8190af7c69dd17ea75fe |
completed | May 2, 2026, 2:53 p.m. |
Created at: April 8, 2026, 9:52 p.m.