Triple
T14171575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ingrid Mössinger |
E351219
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mössinger |
E351219
|
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: Mössinger | Statement: [Ingrid Mössinger, familyName, Mössinger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mössinger Context triple: [Ingrid Mössinger, familyName, Mössinger]
-
A.
Mössinger
chosen
Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
-
B.
Faulbach
Faulbach is a district (Ortsteil) of the town of Hadamar in the Limburg-Weilburg district of Hesse, Germany.
-
C.
Bösel
Bösel is a municipality in Lower Saxony, Germany, known for its rural character and location within the Cloppenburg district.
-
D.
Münnich
Münnich is a German-language surname borne by various notable individuals, including Hungarian communist politician Ferenc Münnich.
-
E.
Maschteich
Maschteich is an artificial pond in Hanover, Germany, situated in the Maschpark near the New Town Hall and known for its scenic urban green setting.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b5dcbc8190b0cfcce5e6c6d582 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4674da8881909dc6c1c8a36cf78e |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:01 a.m.