Triple
T18859331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drammensfjord |
E461266
|
entity |
| Predicate | hasCityOnShore |
P969
|
FINISHED |
| Object | Hurum |
—
|
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: Hurum | Statement: [Drammensfjord, hasCityOnShore, Hurum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hurum Context triple: [Drammensfjord, hasCityOnShore, Hurum]
-
A.
Hurum
chosen
Hurum is a former municipality in southeastern Norway, located on the Hurum Peninsula between the Oslofjord and Drammensfjord.
-
B.
Orhaneli
Orhaneli is a town and district in northwestern Turkey known for its rural character and location within Bursa Province.
-
C.
Harur
Harur is a town in the Indian state of Tamil Nadu known for its role as a local commercial and administrative center within the Dharmapuri region.
-
D.
Ahlat
Ahlat is a historic town in eastern Turkey renowned for its medieval Seljuk-era cemeteries and monuments on the northwestern shore of Lake Van.
-
E.
Hansaray
Hansaray is a historic Crimean Tatar palace complex in Bakhchisarai that served as the residence of the Crimean Khans and a major cultural and political center.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c05fb800819098951ec134a1fa2a |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 10, 2026, 11:57 a.m.