Triple
T4111862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol Abrams |
E90193
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Gerald W. Abrams |
E213750
|
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: Gerald W. Abrams | Statement: [Carol Abrams, spouse, Gerald W. Abrams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerald W. Abrams Context triple: [Carol Abrams, spouse, Gerald W. Abrams]
-
A.
Gerald W. Abrams
chosen
Gerald W. Abrams is an American television producer known for his work on TV movies and series and as the father of filmmaker J. J. Abrams.
-
B.
Edward A. Garmatz
Edward A. Garmatz was a long-serving U.S. Congressman from Maryland who represented Baltimore in the House of Representatives in the mid-20th century.
-
C.
George A. Bermann
George A. Bermann is a prominent American legal scholar and expert in international and comparative law, particularly known for his work in international arbitration.
-
D.
Gerald B. Greenberg
Gerald B. Greenberg is an American film editor best known for his Academy Award–winning work on the 1979 drama "Kramer vs. Kramer."
-
E.
Edward S. Feldman
Edward S. Feldman is an American film producer known for overseeing a range of notable movies across several decades, including acclaimed dramas and thrillers.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01decd808190b4e5a5f76b090b0a |
completed | March 9, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf32f31ecc81909cb29b762481b08e |
completed | March 22, 2026, 12:08 a.m. |
Created at: March 9, 2026, 3:41 p.m.