Triple
T22803725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fishlegs Ingerman |
E564471
|
entity |
| Predicate | homeLocation |
P75
|
FINISHED |
| Object | Berk |
—
|
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: Berk | Statement: [Fishlegs Ingerman, homeLocation, Berk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berk Context triple: [Fishlegs Ingerman, homeLocation, Berk]
-
A.
Berk
Berk is a Turkish surname shared by various individuals, including the notable poet İlhan Berk.
-
B.
Berk
chosen
Berk is the remote Viking island village that serves as the primary setting in the How to Train Your Dragon franchise.
-
C.
Berkheim
Berkheim is a small municipality in the district of Biberach in the federal state of Baden-Württemberg in southern Germany.
-
D.
Berken
Berken is a small municipality in the Oberaargau region of the canton of Bern in Switzerland.
-
E.
Berns
Berns is the surname of Alison Berns, an American former radio and television personality best known for her long-term marriage to broadcaster Howard Stern.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5a7c2881909a7aaacddd09f00c |
completed | April 29, 2026, 3:39 a.m. |
Created at: April 17, 2026, 3:31 p.m.