Triple
T14958945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenka Peterson |
E373007
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lenka |
E736056
|
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: Lenka | Statement: [Lenka Peterson, givenName, Lenka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenka Context triple: [Lenka Peterson, givenName, Lenka]
-
A.
Lenka
chosen
Lenka is a feminine given name, commonly used in Slavic countries, often as a diminutive or variant of names like Elena or Helena.
-
B.
Libuše
Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
-
C.
Nadiža
Nadiža is a river in the western Balkans, known for its clear waters and scenic course through the mountainous border region between Slovenia and Italy.
-
D.
Alena
Alena is a feminine given name commonly used in Slavic countries, often considered a variant of Helena or Magdalena.
-
E.
Lenka Peterson
Lenka Peterson was an American stage, film, and television actress known for her versatile character roles from the mid-20th century onward.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bda691481909c2d89a362782ed8 |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:40 a.m.