Triple
T5077244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jody |
E114427
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Jodey |
E303669
|
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: Jodey | Statement: [Jody, hasSpellingVariant, Jodey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jodey Context triple: [Jody, hasSpellingVariant, Jodey]
-
A.
Jodey Arrington
chosen
Jodey Arrington is a Republican U.S. Representative from Texas known for his conservative positions on fiscal policy, agriculture, and border security.
-
B.
Randall Woodfin
Randall Woodfin is an American politician and attorney who serves as the progressive, reform-focused mayor of Birmingham, Alabama.
-
C.
Jay Garner
Jay Garner is a retired U.S. Army lieutenant general who briefly led the initial U.S.-led civilian administration in Iraq following the 2003 invasion.
-
D.
Affion Crockett
Affion Crockett is an American actor, comedian, and impressionist known for his sketch comedy work and roles in film and television.
-
E.
Clay Hardin
Clay Hardin is a fictional Western gunslinger portrayed by actor Sterling Hayden in the film "Shotgun."
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74f632788190ac4fd047e1a20485 |
completed | March 20, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba6be1248190bad40b869c8d0820 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:39 p.m.