Triple
T10199199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amenemhat I |
E238838
|
entity |
| Predicate | associatedWorkLanguage |
P85137
|
FINISHED |
| Object | Middle Egyptian |
—
|
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: Middle Egyptian | Statement: [Amenemhat I, associatedWorkLanguage, Middle Egyptian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWorkLanguage Context triple: [Amenemhat I, associatedWorkLanguage, Middle Egyptian]
-
A.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
B.
hasWorkedInLanguage
Indicates that an entity has performed work or professional activities using a particular language.
-
C.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
D.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
E.
languageOfUnderlyingWork
chosen
Indicates the language in which the original or underlying work (from which a derived or related work stems) is expressed.
- 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee3dfa108190b2888385ef96de23 |
completed | April 2, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:14 p.m.