Triple
T29417119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimpton Hotels |
E746054
|
entity |
| Predicate | primaryGeographicMarket |
P199907
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Kimpton Hotels, primaryGeographicMarket, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryGeographicMarket Context triple: [Kimpton Hotels, primaryGeographicMarket, United States]
-
A.
primaryTerritory
Indicates that a specified area or region is the main or most important territory associated with an entity.
-
B.
hasPrimaryGeographicScope
chosen
Indicates that an entity is associated with a main or principal geographic area in which it is focused, applicable, or relevant.
-
C.
marketRegion
Indicates the geographic or demographic area in which a product, service, or entity is actively marketed or targeted.
-
D.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
E.
primaryListingMarket
Indicates the market or exchange where a security is first and principally listed for trading.
- 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a01289f781481908f3788f8a719f2f4 |
completed | May 11, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_6a012823c7248190961e20be48dd6246 |
completed | May 11, 2026, 12:51 a.m. |
Created at: April 28, 2026, 3:02 p.m.