Triple
T16102140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | فؤاد الأول |
E390644
|
entity |
| Predicate | التيجان والأوسمة |
P121923
|
FINISHED |
| Object | حمل أوسمة مصرية وأوروبية متعددة |
—
|
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: حمل أوسمة مصرية وأوروبية متعددة | Statement: [فؤاد الأول, التيجان والأوسمة, حمل أوسمة مصرية وأوروبية متعددة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: التيجان والأوسمة Context triple: [فؤاد الأول, التيجان والأوسمة, حمل أوسمة مصرية وأوروبية متعددة]
-
A.
გვარი
Indicates a relationship where one entity is the family name or surname of another entity.
-
B.
خيوط التطريز
Indicates the relationship of being threads specifically used for embroidery work.
-
C.
Chi Chi
Indicates a relationship or action involving an entity named "Chi Chi," such as interaction, association, or effect directed to or from Chi Chi.
-
D.
Typer
Indicates that one entity serves as the type or classification for another entity.
-
E.
عدد الحروف
Indicates the relationship that specifies the number of letters contained in a given word or text.
- F. None of above. chosen
Provenance (4 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6976ec8190b499e99b196b0285 |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 5 a.m.