Triple
T34312791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | modern Ihnasya el-Medina |
E880497
|
entity |
| Predicate | hasAncientEgyptianName |
P8488
|
FINISHED |
| Object | Henen-nesut |
—
|
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: Henen-nesut | Statement: [modern Ihnasya el-Medina, hasAncientEgyptianName, Henen-nesut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAncientEgyptianName Context triple: [modern Ihnasya el-Medina, hasAncientEgyptianName, Henen-nesut]
-
A.
ancientEgyptianName
chosen
Indicates that one entity is the ancient Egyptian name or designation historically used for the other entity.
-
B.
hasAncientEthnicName
Indicates that an entity is associated with an ethnic name or designation that originates from ancient times.
-
C.
nameInHieroglyphs
Indicates that an entity’s name is written or represented using hieroglyphic script.
-
D.
hasSerekhName
Indicates that an entity (typically a ruler) possesses a specific serekh name, the early royal name written within a serekh frame.
-
E.
nameInManetho
Indicates that an entity is referred to by a particular name in the historical works attributed to Manetho.
- 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_69f349b8bb6c8190ad12a7957a574f04 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: May 1, 2026, 1:57 a.m.