Triple
T34854936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrasah of Khalif Niyaz-kul gatehouse |
E1004702
|
entity |
| Predicate | towerDecoration |
P57218
|
FINISHED |
| Object | blue domes |
—
|
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: blue domes | Statement: [Madrasah of Khalif Niyaz-kul gatehouse, towerDecoration, blue domes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: towerDecoration Context triple: [Madrasah of Khalif Niyaz-kul gatehouse, towerDecoration, blue domes]
-
A.
towerStyle
Indicates the architectural or design style that characterizes a given tower.
-
B.
towerShape
Indicates that one entity has the physical form or outline of a tower in relation to another entity.
-
C.
towerCharacteristic
chosen
Indicates that a specified characteristic or feature is attributed to a tower.
-
D.
towerAttachment
Indicates that one entity is physically attached to or structurally connected with a tower.
-
E.
tower
Indicates that one entity is a tall, prominent structure rising above its surroundings, often used for observation, support, or communication.
- 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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.