Triple
T12761598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Blockbuster |
E305008
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Hochwald Forest |
E306023
|
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: Hochwald Forest | Statement: [Operation Blockbuster, location, Hochwald Forest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hochwald Forest Context triple: [Operation Blockbuster, location, Hochwald Forest]
-
A.
Reichswald Forest
chosen
Reichswald Forest is a large wooded area in western Germany near the Dutch border, historically notable as the site of intense fighting during World War II.
-
B.
Eichenwald
Eichenwald is the surname of Kurt Eichenwald, an American journalist and author known for his investigative reporting and political commentary.
-
C.
Granitz Forest
Granitz Forest is a scenic woodland area on Germany’s Rügen Island, known for its beech forests, hiking trails, and the historic Granitz Hunting Lodge.
-
D.
Arnsberg Forest
Arnsberg Forest is a large wooded region in North Rhine-Westphalia, Germany, known for its extensive hiking trails, natural landscapes, and protected nature reserves.
-
E.
Wermsdorf Forest
Wermsdorf Forest is a large woodland area in Saxony, Germany, known for its historic hunting grounds and scenic 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8e44188190840cd23d380bf23d |
completed | April 10, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68eb7e8448190a097d40ed8927285 |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:28 p.m.