Triple
T14801422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | موتی مسجد (لال قلعہ، دہلی) |
E347918
|
entity |
| Predicate | تعمیر کا مقصد |
P64674
|
FINISHED |
| Object | شاہی خاندان کے لیے نجی عبادت گاہ |
—
|
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 خاندان کے لیے نجی عبادت گاہ | Statement: [موتی مسجد (لال قلعہ، دہلی), تعمیر کا مقصد, شاہی خاندان کے لیے نجی عبادت گاہ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تعمیر کا مقصد Context triple: [موتی مسجد (لال قلعہ، دہلی), تعمیر کا مقصد, شاہی خاندان کے لیے نجی عبادت گاہ]
-
A.
restorationGoal
Indicates that an action or plan is intended to return something to a previous, original, or improved state or condition.
-
B.
aimOf
chosen
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
C.
repairedIn
Indicates that an item or object underwent repair within a specified location or during a particular time period.
-
D.
aimsToSolve
Indicates an intention or purpose directed toward resolving, addressing, or eliminating a particular problem, challenge, or issue.
-
E.
remedy
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
- 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.