Triple
T16235038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khan-i-Khanan Rahim's tomb |
E394082
|
entity |
| Predicate | hasChhatris |
P109896
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Khan-i-Khanan Rahim's tomb, hasChhatris, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChhatris Context triple: [Khan-i-Khanan Rahim's tomb, hasChhatris, true]
-
A.
hasChhatri
chosen
Indicates that one entity possesses or features a chhatri (a dome-shaped pavilion or canopy structure) in relation to another entity or location.
-
B.
hasGhat
Indicates that a place or location possesses or is associated with a ghat (a series of steps or landing area leading to a body of water).
-
C.
hasGhatCount
Indicates the number of ghats associated with a given entity.
-
D.
hasMatha
Indicates a relationship where one entity possesses, is associated with, or is characterized by a specific matha (monastic institution or religious seat).
-
E.
hasRatha
Indicates that one entity possesses, includes, or is associated with a chariot (ratha) as part of its attributes or composition.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24559af48819092e4b466778b07e2 |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.