Triple
T3259546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strasbourg tramway |
E68375
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Cronenbourg depot
Cronenbourg depot is a major maintenance and storage facility for the Strasbourg tramway network in Strasbourg, France.
|
E341685
|
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: Cronenbourg depot | Statement: [Strasbourg tramway, hasDepot, Cronenbourg depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cronenbourg depot Context triple: [Strasbourg tramway, hasDepot, Cronenbourg 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.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
C.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
D.
Stonebridge Park depot
Stonebridge Park depot is a London Underground maintenance and stabling facility serving trains on the Bakerloo line.
-
E.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
- 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: Cronenbourg depot Triple: [Strasbourg tramway, hasDepot, Cronenbourg depot]
Generated description
Cronenbourg depot is a major maintenance and storage facility for the Strasbourg tramway network in Strasbourg, France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cronenbourg depot Target entity description: Cronenbourg depot is a major maintenance and storage facility for the Strasbourg tramway network in Strasbourg, France.
-
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.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
C.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
D.
Stonebridge Park depot
Stonebridge Park depot is a London Underground maintenance and stabling facility serving trains on the Bakerloo line.
-
E.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
- 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adafa4f40c81909adfd0f7f568e3ce |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ed941cc81909c35853e793d6ce5 |
completed | March 12, 2026, 10 a.m. |
| NEDg | Description generation | batch_69b2900805d08190afbda5ee5e984b71 |
completed | March 12, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2ac4c52d48190a87b1e535c2e8a37 |
completed | March 12, 2026, 12:06 p.m. |
Created at: March 8, 2026, 3:09 p.m.