Triple
T1187173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahmed Aboul Gheit |
E25272
|
entity |
| Predicate | typeOfDiplomat |
P3078
|
FINISHED |
| Object | career diplomat |
—
|
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: career diplomat | Statement: [Ahmed Aboul Gheit, typeOfDiplomat, career diplomat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfDiplomat Context triple: [Ahmed Aboul Gheit, typeOfDiplomat, career diplomat]
-
A.
typeOfDiplomaticRole
chosen
Indicates the specific kind or category of diplomatic position or function that an entity holds in relation to another.
-
B.
diplomaticRole
Indicates that an entity holds or has held an official diplomatic position or function in relation to another entity or context.
-
C.
diplomaticMissionType
Indicates the specific category or nature of a diplomatic mission that characterizes the relationship between the sending and receiving entities.
-
D.
involvesDiplomat
Indicates that a situation, event, or interaction includes the participation or presence of a diplomat as a relevant party.
-
E.
involvedDiplomat
Indicates that a diplomat participated in, was associated with, or played a role in a specified event, interaction, or situation.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd5578b08190bbe4089857fbf166 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.