Triple
T15682860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leiden |
E377622
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Stationsdistrict
Stationsdistrict is a central urban neighborhood of Leiden, Netherlands, known for its proximity to the main railway station and associated commercial and transit functions.
|
E1170823
|
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: Stationsdistrict | Statement: [Leiden, hasPart, Stationsdistrict]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stationsdistrict Context triple: [Leiden, hasPart, Stationsdistrict]
-
A.
Vestamager station
Vestamager station is a Copenhagen Metro station serving as the southern terminus of Line M1 on the island of Amager.
-
B.
Kedzie station
Kedzie station is a Chicago 'L' rapid transit stop on the Brown Line serving the city's Northwest Side.
-
C.
Holmlia Station
Holmlia Station is a railway station in Oslo, Norway, serving the residential district of Holmlia and the surrounding Søndre Nordstrand area.
-
D.
Ablon station
Ablon station is a suburban railway stop in the Paris metropolitan area serving the commune of Ablon-sur-Seine in northern France.
-
E.
Kiest Station
Kiest Station is a Dallas Area Rapid Transit (DART) light rail stop on the Blue Line serving the Kiest Boulevard area in Dallas, Texas.
- 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: Stationsdistrict Triple: [Leiden, hasPart, Stationsdistrict]
Generated description
Stationsdistrict is a central urban neighborhood of Leiden, Netherlands, known for its proximity to the main railway station and associated commercial and transit functions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stationsdistrict Target entity description: Stationsdistrict is a central urban neighborhood of Leiden, Netherlands, known for its proximity to the main railway station and associated commercial and transit functions.
-
A.
Vestamager station
Vestamager station is a Copenhagen Metro station serving as the southern terminus of Line M1 on the island of Amager.
-
B.
Kedzie station
Kedzie station is a Chicago 'L' rapid transit stop on the Brown Line serving the city's Northwest Side.
-
C.
Holmlia Station
Holmlia Station is a railway station in Oslo, Norway, serving the residential district of Holmlia and the surrounding Søndre Nordstrand area.
-
D.
Ablon station
Ablon station is a suburban railway stop in the Paris metropolitan area serving the commune of Ablon-sur-Seine in northern France.
-
E.
Kiest Station
Kiest Station is a Dallas Area Rapid Transit (DART) light rail stop on the Blue Line serving the Kiest Boulevard area in Dallas, Texas.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f31b5b881908e46ecd9fc6048ab |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee4c8688190ae2fefb56171161a |
completed | May 9, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69ff705476008190b6151491bf89654e |
completed | May 9, 2026, 5:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff70ea739081909f63657c8fd6fa81 |
completed | May 9, 2026, 5:37 p.m. |
Created at: April 10, 2026, 4:16 a.m.