Triple
T1319439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malcolm Glazer |
E28181
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Linda Glazer |
E191304
|
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: Linda Glazer | Statement: [Malcolm Glazer, spouse, Linda Glazer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Glazer Context triple: [Malcolm Glazer, spouse, Linda Glazer]
-
A.
Linda Glazer
chosen
Linda Glazer is a member of the Glazer family, known for its prominent business interests including ownership stakes in major sports franchises.
-
B.
Gloria Katz
Gloria Katz was an American screenwriter and producer best known for her collaborations with George Lucas, including work on films like "American Graffiti" and "Star Wars."
-
C.
Nancy Goodman
Nancy Goodman is an American diplomat, businesswoman, and philanthropist best known for founding the Susan G. Komen Breast Cancer Foundation.
-
D.
June Preisser
June Preisser was an American film actress and dancer best known for her energetic supporting roles in 1930s and 1940s Hollywood musicals, often playing peppy, acrobatic teenagers.
-
E.
Judy Zankel
Judy Zankel was a philanthropist and arts patron whose support and legacy are honored through the naming of Zankel Hall at Carnegie Hall.
- 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1780be8819083a9365b8a49305d |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6523d8f4819082396925561acdc4 |
completed | March 10, 2026, 12:26 a.m. |
Created at: March 1, 2026, 7:55 p.m.