Triple
T3971120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | His Girl Friday |
E92336
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Walter Burns |
E322296
|
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: Walter Burns | Statement: [His Girl Friday, character, Walter Burns]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walter Burns Context triple: [His Girl Friday, character, Walter Burns]
-
A.
Walter Burns
chosen
Walter Burns is the fast-talking, manipulative newspaper editor at the center of the classic newsroom comedy "The Front Page."
-
B.
Tim Wentworth
Tim Wentworth is an American business executive known for leading major healthcare and pharmacy-related companies, including serving as CEO of Walgreens Boots Alliance.
-
C.
Walter Newman
Walter Newman was an American screenwriter known for his work on classic films such as "The Magnificent Seven" and "Cat Ballou."
-
D.
Charles Ewing
Charles Ewing was a 19th-century American lawyer, Union Army general in the Civil War, and later a federal official, known as a prominent member of the influential Ewing family.
-
E.
Charles Belcher
Charles Belcher was an American character actor of the silent film era, known for supporting roles in early 20th-century 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef995d27881908b24a5b2ef57455f |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5400b75d081909b8e4840b15d19f1 |
completed | March 14, 2026, 11:01 a.m. |
Created at: March 9, 2026, 3:32 p.m.