Triple
T10847458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transilien Line N |
E256049
|
entity |
| Predicate | depot |
P14646
|
FINISHED |
| Object |
Trappes depot
Trappes depot is a railway maintenance and stabling facility in Trappes, France, serving trains operating on the Transilien suburban network.
|
E889689
|
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: Trappes depot | Statement: [Transilien Line N, depot, Trappes depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trappes depot Context triple: [Transilien Line N, depot, Trappes depot]
-
A.
Fontenay-sous-Bois depot
Fontenay-sous-Bois depot is a maintenance and storage facility serving trains on Paris Métro Line 1, located in the eastern suburb of Fontenay-sous-Bois.
-
B.
Châtillon-Montrouge depot
Châtillon-Montrouge depot is a major Paris Métro maintenance and storage facility, notably serving rolling stock such as the MF 77 trains.
-
C.
Bachet depot
Bachet depot is a major tram maintenance and storage facility serving the public transport system in Geneva, Switzerland.
-
D.
Babinière depot
Babinière depot is a maintenance and storage facility serving the tramway network in the Nantes metropolitan area of France.
-
E.
Massy
Massy is a suburban town in the southern outskirts of Paris, France, known as a significant transport hub with major RER and TGV connections.
- 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: Trappes depot Triple: [Transilien Line N, depot, Trappes depot]
Generated description
Trappes depot is a railway maintenance and stabling facility in Trappes, France, serving trains operating on the Transilien suburban network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trappes depot Target entity description: Trappes depot is a railway maintenance and stabling facility in Trappes, France, serving trains operating on the Transilien suburban network.
-
A.
Fontenay-sous-Bois depot
Fontenay-sous-Bois depot is a maintenance and storage facility serving trains on Paris Métro Line 1, located in the eastern suburb of Fontenay-sous-Bois.
-
B.
Châtillon-Montrouge depot
Châtillon-Montrouge depot is a major Paris Métro maintenance and storage facility, notably serving rolling stock such as the MF 77 trains.
-
C.
Bachet depot
Bachet depot is a major tram maintenance and storage facility serving the public transport system in Geneva, Switzerland.
-
D.
Babinière depot
Babinière depot is a maintenance and storage facility serving the tramway network in the Nantes metropolitan area of France.
-
E.
Massy
Massy is a suburban town in the southern outskirts of Paris, France, known as a significant transport hub with major RER and TGV connections.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75113bc188190ac78df0c51d95de6 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb170e714819097babb2b850342d2 |
completed | April 14, 2026, 9:28 p.m. |
| NEDg | Description generation | batch_69dec255abb08190bf93573c41aa35e9 |
completed | April 14, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dec7c48c3c81909365b901830f0906 |
completed | April 14, 2026, 11:03 p.m. |
Created at: April 8, 2026, 9:20 p.m.