Triple
T17275295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Karelia |
E419374
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Kem |
E852187
|
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: Kem | Statement: [East Karelia, hasMajorCity, Kem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kem Context triple: [East Karelia, hasMajorCity, Kem]
-
A.
Kem
chosen
Kem is a historic town and seaport in northern Russia on the White Sea, long associated with Pomor seafaring and trade.
-
B.
KEM
KEM is the National Rail station code for Kemble railway station in Gloucestershire, England.
-
C.
KEM
KEM is the IATA airport code for Kemi-Tornio Airport in northern Finland.
-
D.
Kem Likasu
Kem Likasu is a Congolese refugee and medical student who becomes a close colleague and love interest of Dr. John Carter on the television series "ER."
-
E.
Kiesen
Kiesen is a municipality in the canton of Bern, Switzerland, served by a station on the Bern–Thun railway line.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e4332566c08190b4495dbbfe310ab6 |
completed | April 19, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794f6cf481909d76e3d61f9888c5 |
completed | May 11, 2026, 6:38 a.m. |
Created at: April 10, 2026, 5:40 a.m.