Triple
T15347407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferenc Münnich |
E366958
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Münnich |
E366958
|
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: Münnich | Statement: [Ferenc Münnich, familyName, Münnich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Münnich Context triple: [Ferenc Münnich, familyName, Münnich]
-
A.
Münnich
chosen
Münnich is a German-language surname borne by various notable individuals, including Hungarian communist politician Ferenc Münnich.
-
B.
Münsing
Münsing is a municipality in Bavaria, Germany, located near Lake Starnberg and known for its scenic rural landscape and proximity to the Alps.
-
C.
Ködnitz
Ködnitz is a small municipality in northern Bavaria, Germany, known for its rural character within the Franconian region.
-
D.
Morschen
Morschen is a small settlement in the German region historically associated with the Province of Westphalia.
-
E.
Mössinger
Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e1749bc8190a8b9cbcb27288a5b |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1341033881909121ade33cecaf50 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:17 a.m.