Triple
T14467362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Kesselsdorf |
E358747
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Kesselsdorf |
E1157597
|
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: Kesselsdorf | Statement: [Battle of Kesselsdorf, namedAfter, Kesselsdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kesselsdorf Context triple: [Battle of Kesselsdorf, namedAfter, Kesselsdorf]
-
A.
Kesselsdorf
chosen
Kesselsdorf is a village in Saxony, Germany, historically notable as the site of a major battle during the Second Silesian War.
-
B.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
C.
Ebersdorf
Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
-
D.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
-
E.
Siegsdorf
Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f8613c819080424104c0b7f4c3 |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2ce36ce08190930e791e2837d1a5 |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 1:19 a.m.