Triple
T1443360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam Metro line 53 |
E31122
|
entity |
| Predicate | depot |
P14646
|
FINISHED |
| Object |
Gaasperplas depot
Gaasperplas depot is a maintenance and storage facility for Amsterdam Metro trains serving the eastern Gaasperplas line.
|
E165426
|
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: Gaasperplas depot | Statement: [Amsterdam Metro line 53, depot, Gaasperplas depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaasperplas depot Context triple: [Amsterdam Metro line 53, depot, Gaasperplas depot]
-
A.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
B.
Muntplein
Muntplein is a central square in Amsterdam, known as a busy traffic hub near the historic city center and the Munttoren (Mint Tower).
-
C.
Stationsplein
Stationsplein is the main square in front of Amsterdam Centraal Station, serving as a busy hub for trams, buses, taxis, cyclists, and pedestrians entering the city center.
-
D.
Grefsen depot
Grefsen depot is a major tram depot in Oslo, Norway, serving as a key maintenance and storage facility for the city’s tram network.
-
E.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
- 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: Gaasperplas depot Triple: [Amsterdam Metro line 53, depot, Gaasperplas depot]
Generated description
Gaasperplas depot is a maintenance and storage facility for Amsterdam Metro trains serving the eastern Gaasperplas line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gaasperplas depot Target entity description: Gaasperplas depot is a maintenance and storage facility for Amsterdam Metro trains serving the eastern Gaasperplas line.
-
A.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
B.
Muntplein
Muntplein is a central square in Amsterdam, known as a busy traffic hub near the historic city center and the Munttoren (Mint Tower).
-
C.
Stationsplein
Stationsplein is the main square in front of Amsterdam Centraal Station, serving as a busy hub for trams, buses, taxis, cyclists, and pedestrians entering the city center.
-
D.
Grefsen depot
Grefsen depot is a major tram depot in Oslo, Norway, serving as a key maintenance and storage facility for the city’s tram network.
-
E.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c533a158819084d0917776edb6e5 |
completed | March 1, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08be450c8190bc0b8a69733a0bd4 |
completed | March 8, 2026, 5:27 a.m. |
| NEDg | Description generation | batch_69ad09823ce481908b5db3ee9ebd1a88 |
completed | March 8, 2026, 5:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad0a8f17888190913c06641a6ac060 |
completed | March 8, 2026, 5:35 a.m. |
Created at: March 1, 2026, 8 p.m.