Triple
T17389564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto Gessler |
E422780
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gessler |
—
|
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: Gessler | Statement: [Otto Gessler, familyName, Gessler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gessler Context triple: [Otto Gessler, familyName, Gessler]
-
A.
Gessler
chosen
Gessler is a fictional character best known as the tyrannical Austrian bailiff and antagonist in the William Tell legend.
-
B.
Küfferle
Küfferle is a confectionery brand known for its chocolate products and is owned by the Swiss chocolatier Lindt & Sprüngli.
-
C.
Falko
Falko is a given name and variant of "Falco," used in various European countries, particularly in German-speaking regions.
-
D.
Willy Hameister
Willy Hameister was a German cinematographer best known for his influential work on early Expressionist cinema, including the landmark film "The Cabinet of Dr. Caligari."
-
E.
Obertor
Obertor is a historic city gate in Neuss, Germany, notable as one of the town’s best-preserved medieval fortification structures.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a8c718c81909cb20749aaf12897 |
completed | April 19, 2026, 2:14 a.m. |
Created at: April 10, 2026, 5:45 a.m.