Triple
T35279295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Region |
E1018890
|
entity |
| Predicate | containsLargeMetropolitanArea |
P35166
|
FINISHED |
| Object | Dallas–Fort Worth metroplex |
—
|
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: Dallas–Fort Worth metroplex | Statement: [South Region, containsLargeMetropolitanArea, Dallas–Fort Worth metroplex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsLargeMetropolitanArea Context triple: [South Region, containsLargeMetropolitanArea, Dallas–Fort Worth metroplex]
-
A.
isMetropolitanArea
Indicates that a given area functions as a major urban center and its surrounding region, typically characterized by high population density and integrated economic and social activities.
-
B.
includesMajorMetropolitanArea
chosen
Indicates that one entity geographically contains or encompasses a major metropolitan area within its boundaries.
-
C.
isOneOfLargestMetropolitanAreasIn
Indicates that an entity ranks among the largest metropolitan areas within a specified geographic region or jurisdiction.
-
D.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
E.
hasMetropolitanAreaType
Indicates that an entity is associated with a specific type or classification of metropolitan area (e.g., urban, suburban, metropolitan region category).
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00bb3a6f888190b3ecd0fbc9af9b4a |
completed | May 10, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_6a00b902dbf881909e098ff102b7ea7e |
completed | May 10, 2026, 4:57 p.m. |
Created at: May 3, 2026, 4:02 p.m.