Triple
T2959605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konradshöhe |
E80013
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Heiligensee |
E78332
|
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: Heiligensee | Statement: [Konradshöhe, borders, Heiligensee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heiligensee Context triple: [Konradshöhe, borders, Heiligensee]
-
A.
Heiligensee
chosen
Heiligensee is a residential and partly lakeside locality in the northwest of Berlin, known for its green spaces and village-like character within the borough of Reinickendorf.
-
B.
Schlachtensee
Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
-
C.
Müggelsee
Müggelsee is the largest lake in Berlin, Germany, known for its popular recreational areas and natural surroundings.
-
D.
Schwielowsee
Schwielowsee is a scenic lake and municipality in Brandenburg, Germany, known for its natural landscapes, water recreation, and proximity to Potsdam.
-
E.
Lake Müritz
Lake Müritz is Germany’s second-largest lake and a central feature of the Mecklenburg Lake District, known for its extensive wetlands, rich birdlife, and surrounding protected landscapes.
- 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992dd4248190b5f3d4f342593b8c |
completed | March 8, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc923d888190a68075dfaa9e90b2 |
completed | March 11, 2026, 5:24 a.m. |
Created at: March 8, 2026, 2:57 p.m.