Triple
T33652767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City–Cairo |
E862141
|
entity |
| Predicate | typicalDestinationMetropolitanArea |
P89542
|
FINISHED |
| Object | Greater Cairo |
E751952
|
NE 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: Greater Cairo | Statement: [New York City–Cairo, typicalDestinationMetropolitanArea, Greater Cairo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDestinationMetropolitanArea Context triple: [New York City–Cairo, typicalDestinationMetropolitanArea, Greater Cairo]
-
A.
typicalDestinationMetroArea
chosen
Indicates the metro area that is most commonly the destination associated with a given origin or context.
-
B.
typicalOriginMetroArea
Indicates the metropolitan area from which something or someone most commonly originates or is typically sourced.
-
C.
metropolitanAreaWith
Indicates that one entity is a metropolitan area that includes, is associated with, or encompasses the other entity.
-
D.
typicalVenueMetroArea
Indicates the metropolitan area where an entity is most commonly or characteristically located or hosted.
-
E.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
- F. None of above.
Provenance (4 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a365c69cf2c8190a6a6a0645edd6a45 |
completed | June 20, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:42 a.m.