Triple
T14469432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pasila, Helsinki |
E358797
|
entity |
| Predicate | hasRailwayDepot |
P18851
|
FINISHED |
| Object |
Pasila depot
Pasila depot is a major railway maintenance and storage facility serving trains in the Pasila district of Helsinki, Finland.
|
E1101256
|
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: Pasila depot | Statement: [Pasila, Helsinki, hasRailwayDepot, Pasila depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasila depot Context triple: [Pasila, Helsinki, hasRailwayDepot, Pasila depot]
-
A.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
B.
Pajura depot
Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
-
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.
Caolu Depot
Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
-
E.
Pontinha depot
Pontinha 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: Pasila depot Triple: [Pasila, Helsinki, hasRailwayDepot, Pasila depot]
Generated description
Pasila depot is a major railway maintenance and storage facility serving trains in the Pasila district of Helsinki, Finland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pasila depot Target entity description: Pasila depot is a major railway maintenance and storage facility serving trains in the Pasila district of Helsinki, Finland.
-
A.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
B.
Pajura depot
Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
-
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.
Caolu Depot
Caolu Depot is a maintenance and storage facility serving Shanghai Metro’s Line 9 in the Pudong area.
-
E.
Pontinha depot
Pontinha 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f969788190a5114f92d7159aae |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd649beec88190861abb52c5a2733e |
completed | May 8, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_69fd67b1ed2081908d3de6514078be49 |
completed | May 8, 2026, 4:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd682f28948190adc037c18c7deb93 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 10, 2026, 1:20 a.m.