Triple
T18537896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khaba |
E453013
|
entity |
| Predicate | praenomenStatus |
P132054
|
FINISHED |
| Object | uncertain |
—
|
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: uncertain | Statement: [Khaba, praenomenStatus, uncertain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: praenomenStatus Context triple: [Khaba, praenomenStatus, uncertain]
-
A.
praenomenPosition
Indicates the relative ordering or placement of a person's praenomen (given name) within a full name or sequence of names.
-
B.
praenomenCommonlyUsed
Indicates that a particular praenomen (personal first name) is commonly used or frequently occurring within a given context or population.
-
C.
isPraenomenOf
Indicates that a given personal name functions as the praenomen (given name) of a specific individual.
-
D.
praenomenTransliteration
Indicates the transliterated form of a person's Latin praenomen (given name) from its original script into a standardized Latin-letter representation.
-
E.
memberHasPraenomen
Indicates that a member is associated with or bears a specific praenomen (personal given name).
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e534030bd88190b25b95305a12a0c1 |
completed | April 19, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2b93bc8190a6070018d7046547 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:37 a.m.