Triple
T5217045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commander-in-Chief, Egypt |
E117777
|
entity |
| Predicate | hasRankOfOfficeHolder |
P32760
|
FINISHED |
| Object | general |
—
|
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: general | Statement: [Commander-in-Chief, Egypt, hasRankOfOfficeHolder, general]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankOfOfficeHolder Context triple: [Commander-in-Chief, Egypt, hasRankOfOfficeHolder, general]
-
A.
rankHeldByOfficeholder
chosen
Indicates the specific rank or level associated with an office or position that is held by a particular officeholder.
-
B.
hasOfficeHolderType
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
C.
hasListOfOfficeHolders
Indicates that an entity is associated with a collection or record enumerating the individuals who have held a particular office or position.
-
D.
memberHoldsOffice
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
E.
hasHeldOfficeType
Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
- 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_69bd4464ba3c8190bc16b2ebbe42ddb0 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a95abdc8190b0babd79cea1360e |
completed | March 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.