Triple
T33931978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | مكة |
E869919
|
entity |
| Predicate | عدد_الحجاج_سنويا |
P12597
|
FINISHED |
| Object | عدة ملايين من المسلمين |
—
|
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: عدة ملايين من المسلمين | Statement: [مكة, عدد_الحجاج_سنويا, عدة ملايين من المسلمين]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: عدد_الحجاج_سنويا Context triple: [مكة, عدد_الحجاج_سنويا, عدة ملايين من المسلمين]
-
A.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
B.
numberOfTraversalsInHajjSa'i
Indicates the count of times a person moves back and forth between the designated points in the Sa'i ritual during Hajj.
-
C.
performedHajj
Indicates that the subject has completed the Islamic pilgrimage of Hajj.
-
D.
touristArrivalsPerYearApprox
chosen
Indicates an approximate count of how many tourists arrive at a place over the course of a year.
-
E.
numberOfImams
Indicates the count of distinct imams associated with or relevant to a given entity or context.
- 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.