Triple
T4715918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thielle River |
E104637
|
entity |
| Predicate | hasNameInGerman |
P22792
|
FINISHED |
| Object | Zihl |
E301457
|
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: Zihl | Statement: [Thielle River, hasNameInGerman, Zihl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zihl Context triple: [Thielle River, hasNameInGerman, Zihl]
-
A.
Zihl
chosen
Zihl is a river in Switzerland that serves as a key tributary within the Aare river system.
-
B.
Izola
Izola is a coastal town and popular tourist destination on the Adriatic Sea in southwestern Slovenia, known for its fishing heritage and picturesque old town.
-
C.
Fiala
Fiala is a Czech surname most prominently associated with Petr Fiala, the Czech politician and Prime Minister.
-
D.
Nidzica
Nidzica is a historic town in northern Poland known for its well-preserved medieval Teutonic castle and picturesque surroundings.
-
E.
Weisselberg
Weisselberg is a surname most prominently associated with Allen Weisselberg, the longtime chief financial officer of the Trump Organization.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd640a32ec8190850146957885c3cf |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be108440108190a7dc1bbfb27ae6f5 |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:18 p.m.