Triple
T14983698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fletcher Marron |
E373646
|
entity |
| Predicate | relativeOf |
P367
|
FINISHED |
| Object | Rachel Marron |
E75923
|
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: Rachel Marron | Statement: [Fletcher Marron, relativeOf, Rachel Marron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Marron Context triple: [Fletcher Marron, relativeOf, Rachel Marron]
-
A.
Rachel Marron
chosen
Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
-
B.
Elizabeth Dailey
Elizabeth Dailey is known primarily as the spouse of American actor and dancer Dan Dailey.
-
C.
Eileen Morrow
Eileen Morrow is a person notable enough to be recognized as a significant bearer of the surname Morrow.
-
D.
Mary Morello
Mary Morello is an American activist and former schoolteacher best known as the mother of Rage Against the Machine guitarist Tom Morello.
-
E.
Marcia Manon
Marcia Manon was a silent film actress active in the 1910s and 1920s, known for her supporting roles in American dramas and melodramas.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6ff4a7c8190ab7554f3a1a09b67 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f3548b48190aec852723654bd35 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 2:52 a.m.