Triple
T1205982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grunewald forest |
E25888
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Krumme Lanke |
E94247
|
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: Krumme Lanke | Statement: [Grunewald forest, contains, Krumme Lanke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krumme Lanke Context triple: [Grunewald forest, contains, Krumme Lanke]
-
A.
Krumme Lanke
chosen
Krumme Lanke is a lake and popular recreational area in southwestern Berlin, known for its wooded surroundings, bathing spots, and walking trails.
-
B.
Kragstalund
Kragstalund is a residential locality situated within Vallentuna Municipality in Stockholm County, Sweden.
-
C.
De Wolden
De Wolden is a rural municipality in the northeastern Netherlands known for its scenic landscapes, small villages, and agricultural character.
-
D.
Bent Deresi
Bent Deresi is a stream or small river flowing through the Ankara region of Turkey.
-
E.
Schaumainkai
Schaumainkai is a prominent riverside street along the south bank of the Main River in Frankfurt, Germany, known for its concentration of major museums and cultural institutions.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdc314c88190b1b5953834bfce7b |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2e7d28c8190acf5ae2237e6d4e0 |
completed | March 7, 2026, 10:12 p.m. |
Created at: March 1, 2026, 7:46 p.m.