Triple
T33645178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leontine |
E861940
|
entity |
| Predicate | relatedToNameElement |
P205252
|
FINISHED |
| Object | leo |
—
|
LITERAL 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: leo | Statement: [Leontine, relatedToNameElement, leo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToNameElement Context triple: [Leontine, relatedToNameElement, leo]
-
A.
relatedToNameType
Indicates that an entity has a relationship or association with a particular type or category of name.
-
B.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
isRelatedName
Indicates that one name is connected to another through a variant, derivative, or otherwise non-identical but related naming relationship.
-
D.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and another.
-
E.
relatedNamedEntity
Indicates that two entities are connected through a shared or associated proper name (e.g., person, organization, location, or other named entity).
- F. None of above. chosen
Provenance (4 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:42 a.m.