Triple
T3264960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mantua |
E68502
|
entity |
| Predicate | twinCity |
P1072
|
FINISHED |
| Object | Weingarten |
E82476
|
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: Weingarten | Statement: [Mantua, twinCity, Weingarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weingarten Context triple: [Mantua, twinCity, Weingarten]
-
A.
Weingarten
chosen
Weingarten is a small locality within the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
B.
Löwenthal
Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
-
C.
Greenberg
Greenberg is a 2010 indie dramedy film directed by Noah Baumbach and starring Ben Stiller as a troubled man reevaluating his life while housesitting in Los Angeles.
-
D.
Rosenbad
Rosenbad is a prominent government building complex in central Stockholm that houses the offices of the Prime Minister and the Swedish Government.
-
E.
Eisenberg
Eisenberg is a surname most notably associated with American actress Hallie Kate Eisenberg.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcb2da08190a7f4fefdfe6d0098 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ee82a78819082582a24bac97f44 |
completed | March 12, 2026, 10:01 a.m. |
Created at: March 8, 2026, 3:09 p.m.