Triple
T7225399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidency of the Arab Republic of Egypt |
E150365
|
entity |
| Predicate | currentOfficeholderTitle |
P28881
|
FINISHED |
| Object | President of Egypt |
—
|
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: President of Egypt | Statement: [Presidency of the Arab Republic of Egypt, currentOfficeholderTitle, President of Egypt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentOfficeholderTitle Context triple: [Presidency of the Arab Republic of Egypt, currentOfficeholderTitle, President of Egypt]
-
A.
currentOfficeHolderTitle
chosen
Indicates the official title or position name held by the person who currently occupies a given office or role.
-
B.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
C.
headOfLegislatureTitle
Indicates the official title held by the person who serves as the head of a legislature.
-
D.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
E.
notableOfficerTitle
Indicates that an entity holds or is associated with a particularly distinguished or noteworthy officer position or title.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9dc835881909ea646c392a980b6 |
completed | March 27, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.