Triple
T26174242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Lee Burrow |
E654490
|
entity |
| Predicate | playsForCity |
P22309
|
FINISHED |
| Object | Cincinnati, Ohio, 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: Cincinnati, Ohio, United States | Statement: [Joseph Lee Burrow, playsForCity, Cincinnati, Ohio, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsForCity Context triple: [Joseph Lee Burrow, playsForCity, Cincinnati, Ohio, United States]
-
A.
playedForCity
chosen
Indicates that an entity (typically a person or team) has been a member of or represented a sports team or organization based in a particular city.
-
B.
homeCityTeamOf
Indicates that one entity is the sports team based in and representing the home city of the other entity.
-
C.
teamCityOfFranchiseOwned
Indicates that a particular city serves as the home or base city for a sports franchise that is owned by a specified owner.
-
D.
teamPlaysIn
Indicates that a specific sports team participates or competes in a particular league, division, or competition.
-
E.
playsForTitle
Indicates that an entity performs or competes on behalf of a team, organization, or group under a specific title or designation.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6247480cc8190a887eedaeb94615c |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f623a7539c8190b71797f583da9f63 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 26, 2026, 8:37 p.m.