Triple
T33652766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City–Cairo |
E862141
|
entity |
| Predicate | typicalOriginMetropolitanArea |
P89541
|
FINISHED |
| Object | New York metropolitan area |
E7505
|
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: New York metropolitan area | Statement: [New York City–Cairo, typicalOriginMetropolitanArea, New York metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOriginMetropolitanArea Context triple: [New York City–Cairo, typicalOriginMetropolitanArea, New York metropolitan area]
-
A.
typicalOriginMetroArea
chosen
Indicates the metropolitan area from which something or someone most commonly originates or is typically sourced.
-
B.
typicalDestinationMetroArea
Indicates the metro area that is most commonly the destination associated with a given origin or context.
-
C.
hasTypicalGeographicOrigin
Indicates that an entity is commonly or characteristically associated with originating from a particular geographic location.
-
D.
cityOfOriginal
Indicates the city from which something or someone originally comes or was first created or established.
-
E.
typicalVenueMetroArea
Indicates the metropolitan area where an entity is most commonly or characteristically located or hosted.
- 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_6a36271f98708190ae07b4042ad5c8a1 |
completed | June 20, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:42 a.m.