Triple
T36575233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semenkare Nebnuni |
E902228
|
entity |
| Predicate | usesPraenomen |
P109316
|
FINISHED |
| Object | Semenkare |
—
|
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: Semenkare | Statement: [Semenkare Nebnuni, usesPraenomen, Semenkare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPraenomen Context triple: [Semenkare Nebnuni, usesPraenomen, Semenkare]
-
A.
praenomenOrNomen
Indicates that the related name element functions either as a personal given name (praenomen) or as a family/clan name (nomen) within a naming system.
-
B.
isPraenomenOf
Indicates that a given personal name functions as the praenomen (given name) of a specific individual.
-
C.
memberHasPraenomen
chosen
Indicates that a member is associated with or bears a specific praenomen (personal given name).
-
D.
praenomenCommonlyUsed
Indicates that a particular praenomen (personal first name) is commonly used or frequently occurring within a given context or population.
-
E.
praenomenTransliteration
Indicates the transliterated form of a person's Latin praenomen (given name) from its original script into a standardized Latin-letter representation.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:11 p.m.