Triple
T6510943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernst May |
E150130
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | City of Frankfurt am Main |
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: City of Frankfurt am Main | Statement: [Ernst May, employer, City of Frankfurt am Main]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Frankfurt am Main Context triple: [Ernst May, employer, City of Frankfurt am Main]
-
A.
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.
-
B.
Oper Frankfurt
Oper Frankfurt is a major German opera house in Frankfurt am Main, renowned for its high artistic standards and innovative productions.
-
C.
Wiesbaden
Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
-
D.
Stadt Nürnberg
Stadt Nürnberg is the municipal government of the German city of Nuremberg, responsible for local administration, public services, and urban infrastructure.
-
E.
Mannheim
Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f3ad7d081909162f1a625fc52b1 |
completed | March 27, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e40ffb7081908f4dd4679bdefd85 |
completed | March 27, 2026, 8:09 p.m. |
Created at: March 27, 2026, 1:43 p.m.