Triple
T13112065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandenburg-Prussia |
E310995
|
entity |
| Predicate | hasTerritory |
P285
|
FINISHED |
| Object | Cleves |
E102459
|
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: Cleves | Statement: [Brandenburg-Prussia, hasTerritory, Cleves]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cleves Context triple: [Brandenburg-Prussia, hasTerritory, Cleves]
-
A.
Cleves
chosen
Cleves is a historic town in western Germany near the Dutch border, known for its medieval castle and role as a former ducal capital in the Lower Rhine region.
-
B.
Dresden, Ohio
Dresden, Ohio is a small village in Muskingum County known historically as the original home of the Longaberger Company and its handcrafted baskets.
-
C.
Lorain
Lorain is an industrial city on Lake Erie in northern Ohio, historically known for its steel production and shipbuilding.
-
D.
Havana, Ohio
Havana, Ohio is a small unincorporated community located in Huron County in north-central Ohio.
-
E.
Dublin, Ohio
Dublin, Ohio is a suburban city northwest of Columbus known for its affluent neighborhoods, strong school system, and annual Dublin Irish Festival.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817f8ee8819084078b4bec5e4f18 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a82efbb0819081c4eff91303de31 |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:05 p.m.