Triple
T33931965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | مكة |
E869919
|
entity |
| Predicate | مذكورة_في |
P89069
|
FINISHED |
| Object | القرآن الكريم |
—
|
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: القرآن الكريم | Statement: [مكة, مذكورة_في, القرآن الكريم]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مذكورة_في Context triple: [مكة, مذكورة_في, القرآن الكريم]
-
A.
ذُكر_في
chosen
Indicates that an entity is mentioned or referenced within another entity, such as a text, document, or source.
-
B.
notedIn
Indicates that information about one entity is mentioned, recorded, or referenced within another entity, such as a document, record, or source.
-
C.
mentionedInFilm
Indicates that an entity is referenced or talked about within the content of a film.
-
D.
mentionedInParva
Indicates that something is referenced or discussed within a specific parva (section or book) of a larger 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_69f3499a59788190bff762a891471b31 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:49 a.m.