Triple
T13467804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Beveland |
E311547
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Kats |
E355584
|
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: Kats | Statement: [North Beveland, containsSettlement, Kats]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kats Context triple: [North Beveland, containsSettlement, Kats]
-
A.
Kats
chosen
Kats is a small village on the Dutch island of Noord-Beveland in the province of Zeeland, known for its rural character and proximity to the Oosterschelde.
-
B.
KATS
KATS is the electronic trading platform used by the Pakistan Stock Exchange to facilitate and manage securities trading.
-
C.
Kateri
Kateri is a feminine given name most notably associated with Kateri Tekakwitha, the first Native American saint canonized by the Catholic Church.
-
D.
Katt
Katt is the surname of American actor Nicky Katt, known for his character roles in film and television.
-
E.
Kato
Kato is a Japanese surname shared by numerous notable individuals across fields such as entertainment, sports, and politics.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf101a1081909f2aba6da47baacc |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74629f1408190b54194fe794be39a |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:42 p.m.