Triple
T14801426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | موتی مسجد (لال قلعہ، دہلی) |
E347918
|
entity |
| Predicate | تعمیر کے بعد استعمال |
P42452
|
FINISHED |
| Object | شاہی دربار کے افراد کی نماز |
—
|
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: شاہی دربار کے افراد کی نماز | Statement: [موتی مسجد (لال قلعہ، دہلی), تعمیر کے بعد استعمال, شاہی دربار کے افراد کی نماز]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تعمیر کے بعد استعمال Context triple: [موتی مسجد (لال قلعہ، دہلی), تعمیر کے بعد استعمال, شاہی دربار کے افراد کی نماز]
-
A.
subsequentUse
Indicates that one entity is used, applied, or consumed after another entity in time or sequence.
-
B.
useAfterRenovation
chosen
Indicates that something is intended to be used or occupied only after renovation work has been completed.
-
C.
repairedIn
Indicates that an item or object underwent repair within a specified location or during a particular time period.
-
D.
laterRepurposedFor
Indicates that something was originally used for one purpose and subsequently assigned a different, new purpose.
-
E.
reconstructedAfter
Indicates that one entity has been rebuilt, restored, or reassembled following the occurrence or existence of another entity or event.
- 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.