Triple
T16975545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan |
E411799
|
entity |
| Predicate | hasLoveInterest |
P7325
|
FINISHED |
| Object | Bess |
E270201
|
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: Bess | Statement: [Dan, hasLoveInterest, Bess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bess Context triple: [Dan, hasLoveInterest, Bess]
-
A.
Bess
chosen
Bess is a central character in George Gershwin's American folk opera "Porgy and Bess," known as a troubled woman torn between love, addiction, and her harsh surroundings in Catfish Row.
-
B.
Bess
Bess is a character in Louisa May Alcott’s novel "Little Men," which continues the story of the March family from "Little Women."
-
C.
Bess
Bess was the familiar nickname of Elizabeth "Bess" Truman, the First Lady of the United States and wife of President Harry S. Truman.
-
D.
Mollie
Mollie is a young girl in Enid Blyton's "The Wishing-Chair" series who, along with her brother Peter, goes on magical adventures using a flying wishing-chair.
-
E.
Mollie
Mollie was the affectionate nickname of Mary Pinkney Hardy MacArthur, the wife of U.S. General Douglas MacArthur.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d18300c8819080c8bf19962754ba |
completed | April 18, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d4755ffc8190a5c861462e33d526 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.