Triple
T21510629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lukas Heller |
E530708
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lukas |
E202706
|
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: Lukas | Statement: [Lukas Heller, givenName, Lukas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lukas Context triple: [Lukas Heller, givenName, Lukas]
-
A.
Lukas
chosen
Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
-
B.
Lukas Ahorn
Lukas Ahorn was a Swiss sculptor best known for carving Lucerne’s famous Lion Monument, a memorial to the Swiss Guards who died during the French Revolution.
-
C.
Luka
Luka is a masculine given name used in various cultures, often as a form of Luke or Lucas.
-
D.
Luka
Luka is a central character in Maxim Gorky's play "The Lower Depths," known as a compassionate wanderer whose comforting lies and philosophical outlook profoundly affect the other destitute inhabitants of the shelter.
-
E.
Luka
"Luka" is a 1987 folk-pop song by Suzanne Vega that poignantly addresses the subject of child abuse from a child's perspective.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 |
completed | April 23, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09e143c73081908ace3b52a18bdf98 |
completed | May 17, 2026, 3:39 p.m. |
Created at: April 16, 2026, 6:25 p.m.