Triple
T1085087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of a Thousand Minarets |
E24031
|
entity |
| Predicate | denotesFeature |
P6238
|
FINISHED |
| Object | dense concentration of minarets |
—
|
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: dense concentration of minarets | Statement: [City of a Thousand Minarets, denotesFeature, dense concentration of minarets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: denotesFeature Context triple: [City of a Thousand Minarets, denotesFeature, dense concentration of minarets]
-
A.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
B.
keyFeature
Indicates that something is a primary, distinguishing, or most important feature of an entity.
-
C.
withinFeature
Indicates that one entity is spatially contained inside or lies entirely within the bounds of another feature.
-
D.
designationUsedFor
chosen
Indicates that a particular name, label, or title is employed to refer to or identify a specific entity or role.
-
E.
designatorType
Indicates the specific role or category of a designator used to identify or reference an entity within a system or context.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b961d0cc8190858296b44fab2f32 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7407914819092ed933a7316b450 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.