Triple
T21307039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretna, Louisiana |
E525225
|
entity |
| Predicate | isCountyEquivalentSeatOf |
P143674
|
FINISHED |
| Object | Jefferson Parish, Louisiana |
—
|
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: Jefferson Parish, Louisiana | Statement: [Gretna, Louisiana, isCountyEquivalentSeatOf, Jefferson Parish, Louisiana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCountyEquivalentSeatOf Context triple: [Gretna, Louisiana, isCountyEquivalentSeatOf, Jefferson Parish, Louisiana]
-
A.
hasCountySeatOf
Indicates that a place serves as the administrative county seat (capital) of a specified county.
-
B.
hasCountySeatRelation
Indicates that a specific place serves as the county seat (administrative center) of a particular county.
-
C.
hasCountySeatWithRole
Indicates that a county has a designated county seat that fulfills a specific administrative or governmental role.
-
D.
hasCountySeatCounty
Indicates that a county seat is administratively associated with and serves as the seat of government for a specific county.
-
E.
hasCountySeatCity
Indicates that a county has a specific city that serves as its official administrative center or county seat.
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75aa69b40819081e74c042e7cd105 |
completed | April 21, 2026, 11:08 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e6190163448190a2404b396215c686 |
completed | April 20, 2026, 12:16 p.m. |
Created at: April 16, 2026, 4:05 p.m.