Triple
T18008370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Loren Mauldin |
E430812
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Loren Mauldin |
—
|
NE NERFINISHED |
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: Michael Loren Mauldin | Statement: [Michael Loren Mauldin, name, Michael Loren Mauldin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Loren Mauldin Context triple: [Michael Loren Mauldin, name, Michael Loren Mauldin]
-
A.
Michael Loren Mauldin
chosen
Michael Loren Mauldin is an American computer scientist and entrepreneur best known as the creator of the Lycos web search engine.
-
B.
Michael Mauldin
Michael Mauldin is an American music executive and talent manager known for his influential role in the development of contemporary R&B and hip-hop artists.
-
C.
Keith Barish
Keith Barish is an American film producer and financier known for founding Keith Barish Productions and co-founding the Planet Hollywood restaurant chain.
-
D.
Robert Scudder
Robert Scudder is an individual notable enough to be recognized as a significant bearer of the surname Scudder.
-
E.
Nat Mauldin
Nat Mauldin is an American screenwriter and television writer known for his work on family-oriented films and popular TV comedies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b51d44088190bfcd35e532a4c02a |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.