Triple
T12038809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chick Hearn |
E286607
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Marjorie Hearn |
E498868
|
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: Marjorie Hearn | Statement: [Chick Hearn, spouse, Marjorie Hearn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marjorie Hearn Context triple: [Chick Hearn, spouse, Marjorie Hearn]
-
A.
Marjorie Hearn
chosen
Marjorie Hearn was the longtime wife and partner of legendary Los Angeles Lakers broadcaster Chick Hearn.
-
B.
Marjorie Nelson
Marjorie Nelson was an American actress known for her work on stage and screen and for being married to fellow actor Howard Da Silva.
-
C.
Marjorie Vattendahl
Marjorie Vattendahl was the wife of World War II flying ace and Medal of Honor recipient Richard Bong.
-
D.
Marjorie Harvey
Marjorie Harvey is an American fashion enthusiast, socialite, and entrepreneur best known as the wife of comedian and television host Steve Harvey and for her influential presence in fashion and lifestyle media.
-
E.
Marjorie Content
Marjorie Content was an American photographer and writer associated with early 20th-century modernist and literary circles.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040a8be881908f4841145a7b4e86 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef87fbf4c81909a6326f555eb5777 |
completed | May 9, 2026, 9:03 a.m. |
Created at: April 8, 2026, 9:47 p.m.