Triple
T2115975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masjid al-Qiblatayn |
E43810
|
entity |
| Predicate | hasQiblaCount |
P34905
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Masjid al-Qiblatayn, hasQiblaCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQiblaCount Context triple: [Masjid al-Qiblatayn, hasQiblaCount, 2]
-
A.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
B.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
C.
approxElevationAboveMecca
Indicates that one location’s elevation is approximately a specified amount higher or lower than the elevation of Mecca.
-
D.
numberOfRakats
Indicates the specific count of prayer units (rakats) associated with a given prayer or ritual act.
-
E.
hasMihrab
Indicates that a structure or space contains or is equipped with a mihrab, the niche indicating the direction of prayer in a mosque or Islamic prayer area.
- F. None of above. chosen
Provenance (4 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb2dfd3c81909b5e2996bc324301 |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bbf9d881909d223b0cab7cab18 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:43 p.m.