Triple
T3381517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wedding |
E71194
|
entity |
| Predicate | hasGreenSpace |
P1495
|
FINISHED |
| Object | Volkspark Rehberge |
E353644
|
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: Volkspark Rehberge | Statement: [Wedding, hasGreenSpace, Volkspark Rehberge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volkspark Rehberge Context triple: [Wedding, hasGreenSpace, Volkspark Rehberge]
-
A.
Volkspark Rehberge
chosen
Volkspark Rehberge is a large public park in Berlin known for its expansive green spaces, woodlands, and recreational facilities.
-
B.
Kronenburgerpark
Kronenburgerpark is a historic public park in the Dutch city of Nijmegen, known for its medieval city wall, tower, and scenic green spaces.
-
C.
Hofwiesenpark
Hofwiesenpark is a large riverside public park in the city of Gera, Germany, known for its recreational facilities, green spaces, and role as a venue for local events and festivals.
-
D.
Stadtpark
Stadtpark is a large, historic public park in central Vienna, Austria, known for its landscaped gardens and famous monuments such as the Johann Strauss II statue.
-
E.
Riedergarten
Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5e9af608190bfb228ef99a87bb7 |
completed | March 8, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bc3f13c81909bec375bd080b7f3 |
completed | March 12, 2026, 11:27 p.m. |
Created at: March 8, 2026, 3:14 p.m.