Triple
T4259572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villeurbanne |
E96069
|
entity |
| Predicate | hasTramLine |
P17788
|
FINISHED |
| Object |
T4
T4 is a tram line serving the city of Villeurbanne as part of the Lyon metropolitan public transport network in France.
|
E427442
|
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: T4 | Statement: [Villeurbanne, hasTramLine, T4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T4 Context triple: [Villeurbanne, hasTramLine, T4]
-
A.
T4
T4 is one of the lines of the Athens tram system, providing urban light-rail service across part of the Athens metropolitan area.
-
B.
T4
T4 is a light rail/tram line of the Trambesòs network serving the Barcelona metropolitan area.
-
C.
T4
T4 is a tram line that forms part of the urban light rail network serving the city of Casablanca, Morocco.
-
D.
T3
T3 is one of the main lines of the Athens tram system, providing light rail service that connects key coastal and urban areas of the city.
-
E.
T3
T3 is a tram line within the Casablanca Tramway network that serves as one of the city’s main urban light rail routes.
- 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: T4 Triple: [Villeurbanne, hasTramLine, T4]
Generated description
T4 is a tram line serving the city of Villeurbanne as part of the Lyon metropolitan public transport network in France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T4 Target entity description: T4 is a tram line serving the city of Villeurbanne as part of the Lyon metropolitan public transport network in France.
-
A.
T4
T4 is a light rail/tram line of the Trambesòs network serving the Barcelona metropolitan area.
-
B.
T4
T4 is one of the lines of the Athens tram system, providing urban light-rail service across part of the Athens metropolitan area.
-
C.
T4
T4 is a tram line that forms part of the urban light rail network serving the city of Casablanca, Morocco.
-
D.
T3
T3 is one of the main lines of the Athens tram system, providing light rail service that connects key coastal and urban areas of the city.
-
E.
T3
T3 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f7fe7348190baed8d214268b756 |
completed | March 12, 2026, 11:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b78825508190b2b6ca46c8e1b27c |
completed | March 14, 2026, 7:31 p.m. |
| NEDg | Description generation | batch_69b5b84b58a081909618d0c108317f92 |
completed | March 14, 2026, 7:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5b8be90c88190a4852c625e326f6b |
completed | March 14, 2026, 7:36 p.m. |
Created at: March 12, 2026, 11:06 p.m.