Triple
T6676173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (Dubai Metro) |
E151856
|
entity |
| Predicate | servesDistrictType |
P68386
|
FINISHED |
| Object | commercial districts |
—
|
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: commercial districts | Statement: [Red Line (Dubai Metro), servesDistrictType, commercial districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesDistrictType Context triple: [Red Line (Dubai Metro), servesDistrictType, commercial districts]
-
A.
servedDistrict
Indicates that an entity has provided official service or representation to a particular district.
-
B.
electoralDistrictType
Indicates the specific category or kind of electoral district associated with an entity (e.g., federal, state, local).
-
C.
servesStateOrDistrict
Indicates that an entity holds a role or position in service to a specific state or electoral district.
-
D.
cityServedType
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
-
E.
areaServedType
chosen
Indicates the type or category of area that is served by an entity or service.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.