Triple
T32961612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Souq Dakhel |
E843252
|
entity |
| Predicate | belongsToUrbanType |
P85719
|
FINISHED |
| Object | medina square |
—
|
NE NERFINISHED |
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: medina square | Statement: [Souq Dakhel, belongsToUrbanType, medina square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToUrbanType Context triple: [Souq Dakhel, belongsToUrbanType, medina square]
-
A.
belongsToCityType
Indicates that one entity is classified under, or associated with, a particular type or category of city.
-
B.
belongsToUrbanZone
chosen
Indicates that something is located within, or is a part of, a designated urban zone or area.
-
C.
appliesToUrbanAreaType
Indicates that something (such as a rule, measure, or classification) is applicable specifically to a particular type or category of urban area.
-
D.
hasUrbanRelation
Indicates a relationship where one entity is connected to another through an urban context, such as city-based location, influence, or interaction.
-
E.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
- 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_69f3494af2808190ad98cec2f1bc0fe6 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
Created at: May 1, 2026, 1:21 a.m.