Triple
T5918363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | فاتن حمامة |
E131636
|
entity |
| Predicate | فازت |
P20470
|
FINISHED |
| Object | جوائز تمثيل عربية ومصرية 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: جوائز تمثيل عربية ومصرية متعددة | Statement: [فاتن حمامة, فازت, جوائز تمثيل عربية ومصرية متعددة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: فازت Context triple: [فاتن حمامة, فازت, جوائز تمثيل عربية ومصرية متعددة]
-
A.
wonFor
Indicates that one entity received an award, prize, or recognition specifically on behalf of or representing another entity.
-
B.
wonBy
chosen
Indicates that a contest, game, or competition is decided in favor of a particular participant or side.
-
C.
victoryIn
Indicates that one entity achieves a win or success in a specific contest, event, or competitive context involving another entity.
-
D.
winningTeam
Indicates which team is the victor in a given competition, game, or contest.
-
E.
wonTitleFrom
Indicates that one entity obtained a title or championship by defeating or surpassing another specific entity who previously held it.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c048fc112c8190b905bf561c9de096 |
completed | March 22, 2026, 7:54 p.m. |
| PD | Predicate disambiguation | batch_69c03352208c8190968efed05a9fd416 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.