Triple
T22527161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الخيط الرفيع |
E556936
|
entity |
| Predicate | يُذكر في |
P89069
|
FINISHED |
| Object | قوائم الأفلام المصرية الكلاسيكية الشهيرة |
—
|
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: قوائم الأفلام المصرية الكلاسيكية الشهيرة | Statement: [الخيط الرفيع, يُذكر في, قوائم الأفلام المصرية الكلاسيكية الشهيرة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يُذكر في Context triple: [الخيط الرفيع, يُذكر في, قوائم الأفلام المصرية الكلاسيكية الشهيرة]
-
A.
ذُكر_في
chosen
Indicates that an entity is mentioned or referenced within another entity, such as a text, document, or source.
-
B.
rememberedFor
Indicates that one entity is known or recognized primarily because of, or in association with, another entity or achievement.
-
C.
notedIn
Indicates that information about one entity is mentioned, recorded, or referenced within another entity, such as a document, record, or source.
-
D.
mentionedInInscription
Indicates that an entity is referenced or named within a specific inscription or inscribed text.
-
E.
mentionedWith
Indicates that two entities are mentioned together or in close association within the same context, such as a document, sentence, or conversation.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed411488190a51320930b9805c2 |
completed | April 29, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.