Triple
T32885285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nishan al-Kamal |
E841180
|
entity |
| Predicate | traditionalRecipientCountry |
P3061
|
FINISHED |
| Object | Egypt |
—
|
NE NERFINISHED |
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: Egypt | Statement: [Nishan al-Kamal, traditionalRecipientCountry, Egypt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalRecipientCountry Context triple: [Nishan al-Kamal, traditionalRecipientCountry, Egypt]
-
A.
recipientCountry
Indicates the country that receives something (such as goods, services, aid, or communication) from another party.
-
B.
recipientNationality
Indicates that the recipient in a relationship or transaction has a specified national affiliation or citizenship.
-
C.
traditionalRecipient
Indicates that one entity is the customary or culturally recognized recipient of something provided or performed by another entity.
-
D.
beneficiaryCountry
chosen
Indicates that one country is the recipient or beneficiary of aid, resources, or advantages provided in a given context.
-
E.
recipientRegion
Indicates the geographic region that receives or is the destination of a transfer, delivery, or directed action.
- 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fec4cffed08190b5e5e7cc0c87493e |
completed | May 9, 2026, 5:23 a.m. |
| PD | Predicate disambiguation | batch_69fec2ea7fe08190bd751b39515f69d1 |
completed | May 9, 2026, 5:15 a.m. |
Created at: May 1, 2026, 1:18 a.m.