Triple
T6210192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vorpommern-Rügen |
E138846
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object | Ummanz |
E141357
|
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: Ummanz | Statement: [Vorpommern-Rügen, hasIsland, Ummanz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ummanz Context triple: [Vorpommern-Rügen, hasIsland, Ummanz]
-
A.
Ummanz
chosen
Ummanz is a small German Baltic Sea island located just off the western coast of Rügen, known for its rural landscape and bird-rich wetlands.
-
B.
Zumwa
Zumwa is the Gbagyi-language name for Zuma Rock, the iconic monolithic inselberg near Abuja, Nigeria.
-
C.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
D.
Kumba
Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
-
E.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
- 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_69c008ada364819096c9e92c74d639b5 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062896f3881909f264bb45badc5d0 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20da55e3c81909a61471b38e88894 |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:21 p.m.