Triple
T1275436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minister of Defence of Egypt |
E27201
|
entity |
| Predicate | officeHolderRank |
P7155
|
FINISHED |
| Object | Field Marshal 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: Field Marshal of Egypt | Statement: [Minister of Defence of Egypt, officeHolderRank, Field Marshal of Egypt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderRank Context triple: [Minister of Defence of Egypt, officeHolderRank, Field Marshal of Egypt]
-
A.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
B.
officeHolderClass
Indicates that a given role or position is held by members belonging to a specified class or category of office holders.
-
C.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
D.
rankHeldByPost
chosen
Indicates that a particular organizational post or position is associated with, or carries, a specific rank.
-
E.
ordinalInOffice
Indicates the numerical order or rank of an individual’s term or tenure in a particular 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.