Triple
T33585462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kheperkara |
E860266
|
entity |
| Predicate | belongsToTitularyElement |
P91895
|
FINISHED |
| Object | prenomen |
—
|
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: prenomen | Statement: [Kheperkara, belongsToTitularyElement, prenomen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToTitularyElement Context triple: [Kheperkara, belongsToTitularyElement, prenomen]
-
A.
hasTitularyElement
chosen
Indicates that an entity includes or is associated with a specific titulary component, such as a formal title, epithet, or honorific element, as part of its designation.
-
B.
belongsToTitleSystem
Indicates that something is part of, or governed by, a particular title system or titling scheme.
-
C.
isTitularSeeOf
Indicates that one ecclesiastical jurisdiction holds the honorary or formal status of being the titular see associated with another entity (such as a bishop or office).
-
D.
hasTitleCharacterRelation
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
E.
hasTitleRelation
Indicates that one entity holds a formal title, designation, or rank in relation to another entity.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff234f32888190a1d800a3bda432eb |
completed | May 9, 2026, 12:06 p.m. |
| PD | Predicate disambiguation | batch_69ff228ae9a0819083f4b97c10b923f4 |
completed | May 9, 2026, 12:03 p.m. |
Created at: May 1, 2026, 1:40 a.m.