Triple
T15046014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staaken |
E379226
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Neu-Staaken |
E379226
|
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: Neu-Staaken | Statement: [Staaken, hasPart, Neu-Staaken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neu-Staaken Context triple: [Staaken, hasPart, Neu-Staaken]
-
A.
Staaken
chosen
Staaken is a locality in western Berlin, Germany, known for its residential areas and historical role as part of the Spandau district near the former inner-German border.
-
B.
Stadshagen
Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
-
C.
Steenbergen
Steenbergen is a municipality and town in the Dutch province of North Brabant, known for its rural landscape and proximity to several major waterways.
-
D.
Steenbergen
Steenbergen is a small village located in the municipality of Noordenveld in the Dutch province of Drenthe.
-
E.
Neuheim
Neuheim is a small Swiss municipality in the canton of Zug, known for its rural character and proximity to larger economic centers.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded830c3c08190a87b81abbbb75377 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9de73614819098b7a88624407d0e |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 3 a.m.