Triple
T16471159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kleine Enz |
E400062
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | de:Kleine Enz |
E400062
|
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: de:Kleine Enz | Statement: [Kleine Enz, hasNameInLanguage, de:Kleine Enz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de:Kleine Enz Context triple: [Kleine Enz, hasNameInLanguage, de:Kleine Enz]
-
A.
Kleine Enz
chosen
Kleine Enz is a small river in Baden-Württemberg, Germany, that serves as a tributary of the Enz.
-
B.
Kleiner
Kleiner is a surname most notably associated with Eugene Kleiner, a pioneering Silicon Valley venture capitalist and co-founder of the firm Kleiner Perkins.
-
C.
Txikiyana
Txikiyana is a dialectal variety of the Tiriyó language spoken by an Indigenous community in the Amazon region of northern South America.
-
D.
Little D
Little D is a colloquial nickname for the city of Denton, Texas, often used in contrast to nearby Dallas, known as "Big D."
-
E.
Kleine Emme
Kleine Emme is a river in central Switzerland that flows through the canton of Lucerne before joining the Reuss River.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd0d2fc81909b68b5afb00f192f |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f5af4308190bd023624de35027f |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:11 a.m.