Triple
T3443617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braunschweig |
E72622
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Oker |
E79320
|
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: Oker | Statement: [Braunschweig, locatedOnRiver, Oker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oker Context triple: [Braunschweig, locatedOnRiver, Oker]
-
A.
Oker
chosen
The Oker is a river in central Germany that flows northward from the Harz Mountains through Lower Saxony before joining the Aller.
-
B.
Okak
Okak is a dialectal variety of the Fang language spoken by Fang communities in Central Africa.
-
C.
Alte Oker
Alte Oker is a former branch of the Oker River in Germany, now a minor watercourse known for its historical and local geographical significance.
-
D.
Owaneco
Owaneco was a prominent Mohegan sachem (chief) known for his leadership and land dealings in colonial New England during the late 17th and early 18th centuries.
-
E.
Oghi
Oghi is a town in Pakistan's Khyber Pakhtunkhwa province, known as a local administrative and commercial center within the Hazara region.
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba2a605c8190a0eafdf6f25b1e38 |
completed | March 8, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360da33e081908630e3f29ea01530 |
completed | March 13, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:16 p.m.