Triple
T12016469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northwestern Louisiana |
E286037
|
entity |
| Predicate | hasCountyEquivalent |
P3911
|
FINISHED |
| Object | Jackson Parish |
E760337
|
NE 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: Jackson Parish | Statement: [Northwestern Louisiana, hasCountyEquivalent, Jackson Parish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jackson Parish Context triple: [Northwestern Louisiana, hasCountyEquivalent, Jackson Parish]
-
A.
Jackson Parish
chosen
Jackson Parish is a rural parish in northern Louisiana known for its small communities, forestry, and agricultural activities.
-
B.
Madison Parish
Madison Parish is a rural parish in northeastern Louisiana known for its agricultural economy and location along the Mississippi River.
-
C.
Lincoln Parish
Lincoln Parish is a north-central Louisiana parish known for its seat in Ruston and as home to Louisiana Tech University.
-
D.
Franklin Parish
Franklin Parish is a rural parish in northeastern Louisiana known for its agriculture-based economy and small-town communities.
-
E.
LaSalle Parish
LaSalle Parish is a rural parish in central Louisiana known for its forests, waterways, and small communities centered around the town of Jena.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915124e4c8190b0264c2a09e3c2f3 |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c6f1e29c8190b073c3293cf68cb2 |
completed | May 3, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:47 p.m.