Triple
T21307049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretna, Louisiana |
E525225
|
entity |
| Predicate | hasPopulationRankInParish |
P1026
|
FINISHED |
| Object | one of the largest cities in Jefferson Parish |
—
|
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 cities in Jefferson Parish | Statement: [Gretna, Louisiana, hasPopulationRankInParish, one of the largest cities in Jefferson Parish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankInParish Context triple: [Gretna, Louisiana, hasPopulationRankInParish, one of the largest cities in Jefferson Parish]
-
A.
parishSeatPopulationRankInParish
Indicates the rank of a parish seat’s population compared to other settlements within the same parish.
-
B.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
C.
hasPopulationRank
chosen
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
boroughPopulation
Indicates the total number of people living within a specific borough.
-
E.
civilParishNumber
Indicates the identifying number assigned to a specific civil parish within an administrative or geographic system.
- 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_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. |
Created at: April 16, 2026, 4:05 p.m.