Triple
T4688348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klaus |
E103973
|
entity |
| Predicate | shortFormOf |
P43
|
FINISHED |
| Object | Nikolaus |
E52441
|
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: Nikolaus | Statement: [Klaus, shortFormOf, Nikolaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nikolaus Context triple: [Klaus, shortFormOf, Nikolaus]
-
A.
Nikolaus
chosen
Nikolaus is the traditional German figure based on Saint Nicholas who brings small gifts to children on the eve of December 6th.
-
B.
Wilhelm
Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
-
C.
Niklaus
Niklaus is a masculine given name of Germanic origin, notably borne by Swiss computer scientist Niklaus Wirth.
-
D.
Gustav
Gustav is a masculine given name of German origin, borne by several notable historical figures including scientists, artists, and royalty.
-
E.
Theodor
Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6397f6888190a9024a51d4d34f2b |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6f9444548190b7457eabbbd9fb25 |
completed | March 21, 2026, 10:14 a.m. |
Created at: March 20, 2026, 1:16 p.m.