Triple
T1433706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cairo–Marsa Matruh line |
E30508
|
entity |
| Predicate | hasEndpointCityRole |
P8234
|
FINISHED |
| Object | Cairo is national capital |
—
|
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: Cairo is national capital | Statement: [Cairo–Marsa Matruh line, hasEndpointCityRole, Cairo is national capital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEndpointCityRole Context triple: [Cairo–Marsa Matruh line, hasEndpointCityRole, Cairo is national capital]
-
A.
hasEndpointCity
Indicates that a route, connection, or path terminates at a particular city as one of its endpoints.
-
B.
hasCityRole
chosen
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
C.
hasUrbanRole
Indicates that an entity plays a specific functional or social role within an urban or city context.
-
D.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
-
E.
hasAssociatedCity
Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c500a9888190a16fbb1ec97a79c9 |
completed | March 1, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69a4c4771c9481908ae47c959debbe77 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.