Triple
T13161637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Parish |
E312740
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kenner |
E949366
|
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: Kenner | Statement: [Jefferson Parish, contains, Kenner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenner Context triple: [Jefferson Parish, contains, Kenner]
-
A.
Kenner
chosen
Kenner is a suburban city in the New Orleans metropolitan area of Louisiana, known for its proximity to Louis Armstrong New Orleans International Airport and the Mississippi River.
-
B.
Kenner Products
Kenner Products was an American toy company best known for producing popular licensed toy lines such as the original Star Wars action figures.
-
C.
Toymaker
The Toymaker is the primary antagonist in the film "Spy Kids 3-D: Game Over," a villainous game designer who traps players inside his virtual reality world.
-
D.
The Vern
The Vern is the informal name for George Washington University's Mount Vernon Campus in Washington, D.C.
-
E.
Klepper
Klepper is the surname of American comedian and television host Jordan Klepper, known for his work on political satire programs such as The Daily Show.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c0a9d348190909fcf45f9d650e4 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaf4cd788190b74cca51b5219bfb |
completed | May 3, 2026, 6:28 a.m. |
Created at: April 9, 2026, 9:12 p.m.