Triple
T19992536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emil Kraepelin |
E494098
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Dorpat |
—
|
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: Dorpat | Statement: [Emil Kraepelin, workLocation, Dorpat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dorpat Context triple: [Emil Kraepelin, workLocation, Dorpat]
-
A.
Viljandi
Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
-
B.
Tartu
chosen
Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
-
C.
Vyborg
Vyborg is a historic port city in northwestern Russia near the Finnish border, known for its medieval castle and long-contested status between Sweden, Finland, and Russia.
-
D.
Jakobstad
Jakobstad is a coastal town and municipality in western Finland known for its bilingual (Finnish and Swedish) heritage and maritime history.
-
E.
Porvoo
Porvoo is a historic coastal city in southern Finland known for its well-preserved wooden Old Town and medieval cathedral.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe10ffc81908c94168b0a8ea9c9 |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:31 p.m.