Triple
T22154644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franconians |
E547502
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Franken |
—
|
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: Franken | Statement: [Franconians, nativeName, Franken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franken Context triple: [Franconians, nativeName, Franken]
-
A.
Franken
chosen
Franken is a culturally rich region in northern Bavaria, Germany, known for its historic towns, traditional festivals, and distinctive Franconian wine and beer.
-
B.
Franken
Franken is the surname of Al Franken, an American comedian, writer, and former U.S. senator from Minnesota.
-
C.
Frankenreiter
Frankenreiter is the surname of Donavon Frankenreiter, an American surfer-turned-singer-songwriter known for his laid-back, folk-rock music style.
-
D.
Dr. Frankenstein
Dr. Frankenstein is a fictional scientist, most famously depicted as the creator of the monster in Mary Shelley’s novel "Frankenstein" and its many film adaptations.
-
E.
Frankenstein's monster (Universal Classic Monster)
Frankenstein's monster (Universal Classic Monster) is the iconic, bolt-necked creature from Universal Pictures’ classic horror films, known for his immense strength, tragic pathos, and enduring influence on popular culture.
- 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f6d5b88190badee2e515a3b633 |
completed | April 28, 2026, 9:43 p.m. |
Created at: April 16, 2026, 8:33 p.m.