Triple
T38021772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Cairo |
E948653
|
entity |
| Predicate | belongsToCountryCapital |
P174026
|
FINISHED |
| Object | Cairo |
—
|
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: Cairo | Statement: [Northern Cairo, belongsToCountryCapital, Cairo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToCountryCapital Context triple: [Northern Cairo, belongsToCountryCapital, Cairo]
-
A.
hasCountryCapitalConnection
Indicates a relationship in which a specific country is associated with its official capital city.
-
B.
hasCountryCapitalContext
Indicates that a specified context or situation relates a country to its capital city, capturing additional information about that country–capital relationship.
-
C.
associatedCountryCapital
Indicates that a country is related to, or paired with, its capital city.
-
D.
hasCountryOfCapital
Indicates that a capital city is associated with or belongs to a specific country.
-
E.
isInCountryWithCapital
chosen
Indicates that an entity is located in a country whose capital city is a specified place.
- 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_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a004b6ad4248190b402a0d01b0ebf83 |
completed | May 10, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_6a004ae736b881908a0efed8f63f982e |
completed | May 10, 2026, 9:07 a.m. |
Created at: May 3, 2026, 4:20 p.m.