Triple
T22336999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago media market |
E552175
|
entity |
| Predicate | rankWithinUS |
P30985
|
FINISHED |
| Object | one of the largest U.S. media markets |
—
|
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: one of the largest U.S. media markets | Statement: [Chicago media market, rankWithinUS, one of the largest U.S. media markets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankWithinUS Context triple: [Chicago media market, rankWithinUS, one of the largest U.S. media markets]
-
A.
frequencyRankInUnitedStates
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
-
B.
nationalRank
chosen
Indicates the position or standing of an entity within a ranking system at the national level.
-
C.
rankInCountry
Indicates the position or standing of an entity within a specific country according to some ranking or ordered criterion.
-
D.
nationalRankingScope
Indicates that the ranking being referred to is evaluated at the national (country-wide) level rather than regional or local scopes.
-
E.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157804e60819094e2a903ace6f4b2 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.