Triple
T14801432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | موتی مسجد (لال قلعہ، دہلی) |
E347918
|
entity |
| Predicate | فنِ تعمیر کی قسم |
P32038
|
FINISHED |
| Object | گنبد اور محرابوں پر مشتمل ڈھانچہ |
—
|
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: گنبد اور محرابوں پر مشتمل ڈھانچہ | Statement: [موتی مسجد (لال قلعہ، دہلی), فنِ تعمیر کی قسم, گنبد اور محرابوں پر مشتمل ڈھانچہ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: فنِ تعمیر کی قسم Context triple: [موتی مسجد (لال قلعہ، دہلی), فنِ تعمیر کی قسم, گنبد اور محرابوں پر مشتمل ڈھانچہ]
-
A.
constructionType
Indicates the specific method or style by which something is built or constructed.
-
B.
typeOfWork
Indicates the kind or category of work associated with or performed by an entity.
-
C.
constructionForm
chosen
Indicates the method, style, or structural technique by which something is built or constructed.
-
D.
typeOfFixing
Indicates the specific method or manner in which one entity is fastened, attached, or secured to another.
-
E.
مادة البناء
Indicates a relationship where something serves as, or is used as, a construction material in building or structural work.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd62c36c81909c2993dc7d1a79ea |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.