Triple
T37785109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercy Field at Lewis and Clark Park |
E941931
|
entity |
| Predicate | hasHomeTeamCity |
P196971
|
FINISHED |
| Object | Sioux City, Iowa |
—
|
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: Sioux City, Iowa | Statement: [Mercy Field at Lewis and Clark Park, hasHomeTeamCity, Sioux City, Iowa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHomeTeamCity Context triple: [Mercy Field at Lewis and Clark Park, hasHomeTeamCity, Sioux City, Iowa]
-
A.
hasHomeCityTeamStadium
Indicates that a sports team’s home city is associated with a specific stadium where the team primarily hosts its home games.
-
B.
team2HomeArenaCity
Indicates the city where the second team’s home arena is located.
-
C.
homeCityTeamOf
Indicates that one entity is the sports team based in and representing the home city of the other entity.
-
D.
locationTeam1City
Indicates the city where the first team involved in the relationship is located.
-
E.
hasHomeCityStadium
Indicates that a sports team or organization has its primary home stadium located in a specific city.
- F. None of above. chosen
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_69f76ee5cb0c81909a363d1c929156c0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe6fea4a288190bf8615c5d6bf41b4 |
completed | May 8, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69fe6f774de08190975a2393b9a1fd22 |
completed | May 8, 2026, 11:19 p.m. |
| PDg | Predicate description generation | batch_69fe6fe98e38819085100ce4c6cee5b8 |
completed | May 8, 2026, 11:21 p.m. |
Created at: May 3, 2026, 4:19 p.m.