Triple
T6914756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Lorenz of Belgium, Archduke of Austria-Este |
E160022
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lorenz |
E275141
|
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: Lorenz | Statement: [Prince Lorenz of Belgium, Archduke of Austria-Este, givenName, Lorenz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorenz Context triple: [Prince Lorenz of Belgium, Archduke of Austria-Este, givenName, Lorenz]
-
A.
Lorenz
chosen
Lorenz is a masculine given name of German origin, historically borne by various notable figures in Europe.
-
B.
Lorenz attractor
The Lorenz attractor is a famous chaotic set arising from a simplified model of atmospheric convection, known for its butterfly-shaped trajectory and role as an early example of deterministic chaos in dynamical systems.
-
C.
Rabinovich
Rabinovich is a Jewish surname of Eastern European origin, notably borne by the Yiddish writer Sholem Aleichem (born Sholem Rabinovich).
-
D.
Loren
Loren is a given name used for people of any gender, often as a variant or shortened form of names like Lorenzo or Lauren.
-
E.
Beltrami
Beltrami is an Italian surname borne by various notable individuals across fields such as music, mathematics, and the arts.
- 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9dda4108190a79a7841b0658a4d |
completed | March 27, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7491116448190b9945e5a53056cb9 |
completed | March 28, 2026, 3:20 a.m. |
Created at: March 27, 2026, 2:26 p.m.