Triple
T34921227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Transit |
E1007142
|
entity |
| Predicate | locatedInMetropolitanPlanningOrganizationArea |
P104946
|
FINISHED |
| Object |
Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes
The Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes is the metropolitan planning organization responsible for coordinating regional transportation and land-use planning across the greater New Orleans area.
|
E2117012
|
NE FINISHED |
How this triple was built (3 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: Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes | Statement: [Jefferson Transit, locatedInMetropolitanPlanningOrganizationArea, Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes Triple: [Jefferson Transit, locatedInMetropolitanPlanningOrganizationArea, Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes]
Generated description
The Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes is the metropolitan planning organization responsible for coordinating regional transportation and land-use planning across the greater New Orleans area.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInMetropolitanPlanningOrganizationArea Context triple: [Jefferson Transit, locatedInMetropolitanPlanningOrganizationArea, Regional Planning Commission for Jefferson, Orleans, Plaquemines, St. Bernard, and St. Tammany Parishes]
-
A.
hasMetropolitanPlanningAuthority
chosen
Indicates that an entity is under the jurisdiction or oversight of a specific metropolitan planning authority responsible for regional planning and development decisions.
-
B.
isWithinMetroArea
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
C.
belongsToMetropolitanRegion
Indicates that one geographic or administrative area is part of, or included within, a larger metropolitan region.
-
D.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
E.
hasMetropolitanCouncil
Indicates that an administrative region or jurisdiction is governed or overseen by a metropolitan council.
- F. None of above.
Provenance (6 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3786f9e55c8190a89f8a6a9a5753d1 |
completed | June 21, 2026, 6:38 a.m. |
| NEDg | Description generation | batch_6a378f9e0e5881909de7792d091ddcdf |
completed | June 21, 2026, 7:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a37906a102c8190a47f112103741b80 |
completed | June 21, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.