Triple
T9220593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | كسوة الكعبة |
E221348
|
entity |
| Predicate | ترتبط بـ |
P37
|
FINISHED |
| Object | مناسك الحج |
—
|
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: مناسك الحج | Statement: [كسوة الكعبة, ترتبط بـ, مناسك الحج]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ترتبط بـ Context triple: [كسوة الكعبة, ترتبط بـ, مناسك الحج]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
C.
relatedToProduct
Indicates a general association or connection between an entity and a specific product, without specifying the exact nature of that relationship.
-
D.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
E.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda75b6888190814cfb890e763b8f |
completed | April 1, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:28 p.m.