Triple
T3264897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rennes |
E68501
|
entity |
| Predicate | hasTransport |
P1298
|
FINISHED |
| Object |
Rennes Metro
Rennes Metro is the rapid transit system serving the city of Rennes in France, providing urban rail transport across the metropolitan area.
|
E341548
|
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: Rennes Metro | Statement: [Rennes, hasTransport, Rennes Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rennes Metro Context triple: [Rennes, hasTransport, Rennes Metro]
-
A.
Rennes metro station
Rennes metro station is a Paris Métro station on Line 12 located in the city's 6th arrondissement, serving the Saint-Germain-des-Prés area on the Left Bank.
-
B.
Nantes tramway
The Nantes tramway is a modern light rail network in Nantes, France, that serves as a key component of the city's public transportation system.
-
C.
Lille Metro
The Lille Metro is a fully automated light metro system serving the city of Lille and its metropolitan area in northern France.
-
D.
Rouen tramway
The Rouen tramway is a light rail and tram system serving the city of Rouen and its suburbs in Normandy, France.
-
E.
Orléans tramway
The Orléans tramway is a modern light rail system serving the city of Orléans, France, providing efficient urban and suburban public transportation.
- 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: Rennes Metro Triple: [Rennes, hasTransport, Rennes Metro]
Generated description
Rennes Metro is the rapid transit system serving the city of Rennes in France, providing urban rail transport across the metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rennes Metro Target entity description: Rennes Metro is the rapid transit system serving the city of Rennes in France, providing urban rail transport across the metropolitan area.
-
A.
Rennes metro station
Rennes metro station is a Paris Métro station on Line 12 located in the city's 6th arrondissement, serving the Saint-Germain-des-Prés area on the Left Bank.
-
B.
Nantes tramway
The Nantes tramway is a modern light rail network in Nantes, France, that serves as a key component of the city's public transportation system.
-
C.
Lille Metro
The Lille Metro is a fully automated light metro system serving the city of Lille and its metropolitan area in northern France.
-
D.
Rouen tramway
The Rouen tramway is a light rail and tram system serving the city of Rouen and its suburbs in Normandy, France.
-
E.
Orléans tramway
The Orléans tramway is a modern light rail system serving the city of Orléans, France, providing efficient urban and suburban public transportation.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcb2da08190a7f4fefdfe6d0098 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ee82a78819082582a24bac97f44 |
completed | March 12, 2026, 10:01 a.m. |
| NEDg | Description generation | batch_69b29015e77481908c8b41fc3f75dd6f |
completed | March 12, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2ac133f648190a4040881db05a353 |
completed | March 12, 2026, 12:05 p.m. |
Created at: March 8, 2026, 3:09 p.m.