Triple
T25804736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worth Township, Boone County, Indiana |
E649935
|
entity |
| Predicate | borderingPoliticalEntityType |
P170615
|
FINISHED |
| Object | other townships of Boone County, Indiana |
—
|
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: other townships of Boone County, Indiana | Statement: [Worth Township, Boone County, Indiana, borderingPoliticalEntityType, other townships of Boone County, Indiana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderingPoliticalEntityType Context triple: [Worth Township, Boone County, Indiana, borderingPoliticalEntityType, other townships of Boone County, Indiana]
-
A.
borderingRepublic
Indicates that one republic shares a land or maritime border with another republic.
-
B.
countryBorderRelation
Indicates that two countries share a common land or maritime boundary with each other.
-
C.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
D.
borderingEntityCountry
Indicates that one country shares a land or maritime boundary with another country.
-
E.
borderingCountryOfState
Indicates that one country shares a land or maritime boundary directly with the specified state.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 22, 2026, 7:02 a.m.