Triple
T11312469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line A (Reims tramway) |
E267872
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Reims tramway |
E54426
|
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: Reims tramway | Statement: [Line A (Reims tramway), partOf, Reims tramway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reims tramway Context triple: [Line A (Reims tramway), partOf, Reims tramway]
-
A.
Tramway de Reims
chosen
Tramway de Reims is the modern light rail tram system serving the city of Reims in northeastern France, providing urban public transportation across the metropolitan area.
-
B.
Valenciennes tramway
The Valenciennes tramway is a modern light rail system serving the city of Valenciennes and its surrounding metropolitan area in northern France.
-
C.
Rouen tramway
The Rouen tramway is a light rail and tram system serving the city of Rouen and its suburbs in Normandy, France.
-
D.
Tramway de Tours
Tramway de Tours is the modern light rail system serving the city of Tours in central France, providing urban and suburban public transportation along dedicated tram lines.
-
E.
Mulhouse tramway
The Mulhouse tramway is a modern light rail network in Mulhouse, France, providing urban and suburban public transport and connecting key districts of the city and its surroundings.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c1b7dc81908d8cc768c47390d3 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5563dc9c881908d17a061e6071d2c |
completed | April 19, 2026, 10:25 p.m. |
Created at: April 8, 2026, 9:32 p.m.