Triple
T5556151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valerie Jarrett |
E145646
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Laura Jarrett |
E179290
|
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: Laura Jarrett | Statement: [Valerie Jarrett, child, Laura Jarrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Jarrett Context triple: [Valerie Jarrett, child, Laura Jarrett]
-
A.
Laura Jarrett
chosen
Laura Jarrett is an American attorney and journalist known for her work as a legal correspondent on major U.S. news networks.
-
B.
Laura Jennings
Laura Jennings is a film editor best known for her work on major action and science fiction movies, including the Tom Cruise–led blockbuster "Edge of Tomorrow."
-
C.
Jennifer McDaniel
Jennifer McDaniel is an American makeup artist best known for her former marriage to professional wrestling icon Hulk Hogan.
-
D.
Sarah Brasfield
Sarah Brasfield is known as the stepchild of American politician and former Nevada governor Jack Carter.
-
E.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ffc5e7c81908e1c454d3bfd357b |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c74872582c81908c64a9bf925f67c6 |
completed | March 28, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:36 p.m.