Triple
T23973856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenzsche Regel |
E604308
|
entity |
| Predicate | hatAlternativeBezeichnung |
P48365
|
FINISHED |
| Object | Lenzsches Gesetz |
—
|
NE NERFINISHED |
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: Lenzsches Gesetz | Statement: [Lenzsche Regel, hatAlternativeBezeichnung, Lenzsches Gesetz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hatAlternativeBezeichnung Context triple: [Lenzsche Regel, hatAlternativeBezeichnung, Lenzsches Gesetz]
-
A.
haveAlternativeTitle
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
B.
altLabel
chosen
Indicates an alternative name, label, or synonym used to refer to the same entity as the primary label.
-
C.
alternativeUsedBy
Indicates that one entity serves as an alternative option or substitute that is used in place of another entity.
-
D.
isAlternativeTo
Indicates that one entity can serve as a substitute or different option in place of another.
-
E.
hasAlternativeToponymy
Indicates that an entity is associated with one or more alternative place names or toponyms used to refer to the same geographic location.
- F. None of above.
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_69e29543019c8190872462e593cc50b4 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d1dda91c8190af716bceb3225aee |
completed | April 29, 2026, 9:39 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:26 p.m.