Triple
T1453806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Mosque |
E31351
|
entity |
| Predicate | hasMihrab |
P28775
|
FINISHED |
| Object | mihrab made of finely carved marble |
—
|
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: mihrab made of finely carved marble | Statement: [Blue Mosque, hasMihrab, mihrab made of finely carved marble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMihrab Context triple: [Blue Mosque, hasMihrab, mihrab made of finely carved marble]
-
A.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
-
B.
hasMinaretHeightApprox
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
-
C.
hasDomeDecoration
Indicates that an entity’s dome is adorned with specific decorative elements or ornamentation.
-
D.
hasMausoleum
Indicates that one entity possesses, contains, or is associated with a mausoleum dedicated to another entity.
-
E.
hasMezzanine
Indicates that one entity includes or is equipped with a mezzanine level in relation to another entity.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57e82d48190a30a4512f39f5de0 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c55508948190922aee3230a4323e |
completed | March 1, 2026, 11:01 p.m. |
Created at: March 1, 2026, 8 p.m.