Triple
T12065799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khentetka |
E287290
|
entity |
| Predicate | nameWrittenInHieroglyphs |
P77948
|
FINISHED |
| Object | ḫntt-k3 |
—
|
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: ḫntt-k3 | Statement: [Khentetka, nameWrittenInHieroglyphs, ḫntt-k3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameWrittenInHieroglyphs Context triple: [Khentetka, nameWrittenInHieroglyphs, ḫntt-k3]
-
A.
nameInHieroglyphs
Indicates that an entity’s name is written or represented using hieroglyphic script.
-
B.
EgyptianVersionInscribedOn
Indicates that an Egyptian-language version of a text or inscription is carved or written onto a particular physical object or surface.
-
C.
nameWrittenIn
chosen
Indicates that an entity’s name is written or recorded using a specified language, script, or writing system.
-
D.
ancientEgyptianName
Indicates that one entity is the ancient Egyptian name or designation historically used for the other entity.
-
E.
pyramidTextInscriptions
Indicates that the subject has text inscriptions located on or within a pyramid.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.