Triple
T15080600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve King |
E380129
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Steve King |
E380129
|
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: Steve King | Statement: [Steve King, name, Steve King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve King Context triple: [Steve King, name, Steve King]
-
A.
Steve King
chosen
Steve King is a former Republican U.S. Representative from Iowa known for his hardline conservative positions and controversial remarks on immigration and race.
-
B.
Stephen King
Stephen King is a prolific American author renowned for his horror, supernatural fiction, suspense, and fantasy novels, many of which have been adapted into successful films and television series.
-
C.
Dean Koontz
Dean Koontz is a bestselling American author known for his suspenseful thrillers that blend horror, mystery, and science fiction elements.
-
D.
Jonathan Rollins
Jonathan Rollins is a high-powered, ambitious attorney on the television series "L.A. Law," known for his sharp legal skills and complex personal relationships.
-
E.
David Koontz
David Koontz is known as the husband of author and actress Christina Crawford, who wrote the memoir "Mommie Dearest."
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff80008c88190840f94222f867478 |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae15d6308190a62b4f66c550db04 |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:03 a.m.