Triple
T1024739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osnabrück |
E22113
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Hase |
E77450
|
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: Hase | Statement: [Osnabrück, river, Hase]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hase Context triple: [Osnabrück, river, Hase]
-
A.
Hase
chosen
The Hase is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia, passing towns such as Quakenbrück before joining the Ems.
-
B.
Hama
Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
-
C.
Havah
Havah is a transliteration of the Hebrew name for Eve, the first woman in the biblical creation narrative.
-
D.
Haya
Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
-
E.
Heage
Heage is a village in Derbyshire, England, best known for its historic stone tower windmill and rural setting.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7e28df08190b5be7794442a6f21 |
completed | March 1, 2026, 10:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bb83118819098a2b283a1cbf8d6 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.