Triple
T1293821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felix Frankfurter |
E27607
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Frankfurter |
E16481
|
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: Frankfurter | Statement: [Felix Frankfurter, familyName, Frankfurter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frankfurter Context triple: [Felix Frankfurter, familyName, Frankfurter]
-
A.
Colognian
Colognian is a Central Ripuarian Franconian dialect of German spoken primarily in and around the city of Cologne.
-
B.
Gothenburger
A Gothenburger is a resident or native of Gothenburg, Sweden’s second-largest city and a major port on the country’s west coast.
-
C.
Weimar
Weimar is a historic German city renowned as a center of culture and the arts, associated with figures like Goethe and Schiller and pivotal movements in modern design and architecture.
-
D.
Frankfurt am Main
chosen
Frankfurt am Main is a major German financial and transportation hub on the River Main, known for hosting the European Central Bank and one of Europe’s busiest airports.
-
E.
Nuremberg dialect
The Nuremberg dialect is a regional variety of East Franconian German traditionally spoken in and around the city of Nuremberg in Bavaria.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0f2eb608190a0ac47a73adae19b |
completed | March 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acacc1e7948190a1ecd240c751d258 |
completed | March 7, 2026, 10:54 p.m. |
Created at: March 1, 2026, 7:51 p.m.