Triple
T4407440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin lake system |
E93768
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Weißer See
Weißer See is a small urban lake and popular recreational spot located in Berlin's Weißensee district.
|
E445696
|
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: Weißer See | Statement: [Berlin lake system, hasPart, Weißer See]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weißer See Context triple: [Berlin lake system, hasPart, Weißer See]
-
A.
Svityaz Lake
Svityaz Lake is the deepest and one of the largest natural lakes in Ukraine, renowned for its clear waters and location within the Shatsk National Nature Park.
-
B.
Solina Lake
Solina Lake is a large artificial reservoir in southeastern Poland, renowned for its scenic mountain setting, hydroelectric dam, and popularity as a tourist and water-sports destination.
-
C.
Heiliger See
Heiliger See is a picturesque lake in Potsdam, Germany, known for its scenic setting amid historic palaces and gardens.
-
D.
Baltic Ice Lake
The Baltic Ice Lake was a large proglacial lake that existed at the end of the last Ice Age in the area now occupied by the northern Baltic Sea.
-
E.
Stadtsee
Stadtsee is a small lake located in the town of Bad Waldsee in southern Germany, known for its scenic setting and recreational use.
- 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: Weißer See Triple: [Berlin lake system, hasPart, Weißer See]
Generated description
Weißer See is a small urban lake and popular recreational spot located in Berlin's Weißensee district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weißer See Target entity description: Weißer See is a small urban lake and popular recreational spot located in Berlin's Weißensee district.
-
A.
Svityaz Lake
Svityaz Lake is the deepest and one of the largest natural lakes in Ukraine, renowned for its clear waters and location within the Shatsk National Nature Park.
-
B.
Solina Lake
Solina Lake is a large artificial reservoir in southeastern Poland, renowned for its scenic mountain setting, hydroelectric dam, and popularity as a tourist and water-sports destination.
-
C.
Heiliger See
Heiliger See is a picturesque lake in Potsdam, Germany, known for its scenic setting amid historic palaces and gardens.
-
D.
Baltic Ice Lake
The Baltic Ice Lake was a large proglacial lake that existed at the end of the last Ice Age in the area now occupied by the northern Baltic Sea.
-
E.
Stadtsee
Stadtsee is a small lake located in the town of Bad Waldsee in southern Germany, known for its scenic setting and recreational use.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3548b1ca08190b3136867c7098d86 |
completed | March 13, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bb80cd81d08190ad1d65091cecdfac |
completed | March 19, 2026, 4:51 a.m. |
| NEDg | Description generation | batch_69bb839526c48190adeb2a8bccc82ff2 |
completed | March 19, 2026, 5:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bb83ddb6ac8190bb5d48b27f2511b1 |
completed | March 19, 2026, 5:04 a.m. |
Created at: March 12, 2026, 11:28 p.m.