Triple
T4950335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Benchley |
E111153
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Benchley |
E111149
|
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: Benchley | Statement: [Robert Benchley, familyName, Benchley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benchley Context triple: [Robert Benchley, familyName, Benchley]
-
A.
Benchley
chosen
Benchley is the surname of Peter Benchley, the American author best known for writing the novel "Jaws."
-
B.
Nathaniel Benchley
Nathaniel Benchley was an American author and screenwriter known for his humorous novels and stories, several of which were adapted into popular films.
-
C.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
-
D.
Barron
Barron is a surname of English origin borne by various notable individuals across fields such as law, politics, and the arts.
-
E.
Ray Teal
Ray Teal was an American character actor best known for his prolific work in mid-20th-century film and television, including numerous Westerns and supporting roles in major Hollywood productions.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7167f97481908db5bfa9338e3824 |
completed | March 20, 2026, 4:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be89eefa5c8190871debbb8fe6dabe |
completed | March 21, 2026, 12:07 p.m. |
Created at: March 20, 2026, 1:31 p.m.