Triple
T15737862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadion metro station |
E381520
|
entity |
| Predicate | servesBorough |
P82
|
FINISHED |
| Object | Innerstaden |
E902144
|
NE FINISHED |
How this triple was built (2 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: Innerstaden | Statement: [Stadion metro station, servesBorough, Innerstaden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Innerstaden Context triple: [Stadion metro station, servesBorough, Innerstaden]
-
A.
Innerstaden
chosen
Innerstaden is a central district of Malmö, Sweden, encompassing parts of the city’s historic core and key cultural and commercial areas.
-
B.
Innenstadt
Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
-
C.
Innere Stadt
Innere Stadt is the historic first district and city center of Vienna, Austria, known for its medieval street layout, grand boulevards, and concentration of major cultural and political landmarks.
-
D.
Stadtmitte
Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
-
E.
Stadtmitte
Stadtmitte is the central urban district of the town of Bad Honnef in North Rhine-Westphalia, Germany.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd6eb888190b7a9b07b76e62c0d |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff830336248190a8bbd8153dd95daa |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:46 a.m.