Triple
T23247229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forchtenberg |
E581613
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Kocher |
—
|
NE NERFINISHED |
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: Kocher | Statement: [Forchtenberg, locatedOnRiver, Kocher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kocher Context triple: [Forchtenberg, locatedOnRiver, Kocher]
-
A.
Kocher
Kocher is a Swiss surname most notably associated with Nobel Prize–winning surgeon Emil Theodor Kocher.
-
B.
Kocher
chosen
The Kocher is a river in the German state of Baden-Württemberg that flows through towns such as Aalen and Schwäbisch Hall before joining the Neckar.
-
C.
Guerin
Guerin is a surname of French origin borne by various notable individuals across fields such as arts, sports, and public life.
-
D.
Kienbaum
Kienbaum is a small village in the municipality of Grünheide (Mark) in Brandenburg, Germany, known in part for its nearby national Olympic training center.
-
E.
Meyerhof
Meyerhof is a surname of German origin, notably borne by biochemist Otto Fritz Meyerhof, a Nobel laureate recognized for his work on muscle metabolism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f1e8448190b8420a8dc6e24576 |
completed | April 29, 2026, 5:15 a.m. |
Created at: April 17, 2026, 4:10 p.m.