Triple
T3971121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | His Girl Friday |
E92336
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Hildy Johnson |
E323997
|
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: Hildy Johnson | Statement: [His Girl Friday, character, Hildy Johnson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hildy Johnson Context triple: [His Girl Friday, character, Hildy Johnson]
-
A.
Hildy Johnson
chosen
Hildy Johnson is the fast-talking, ambitious newspaper reporter at the center of the classic newsroom comedy "The Front Page."
-
B.
Hildy Beyeler
Hildy Beyeler is a Swiss art patron known for co-founding the renowned Beyeler Foundation Museum, which houses one of Europe’s leading collections of modern and contemporary art.
-
C.
Hildy
Hildy is a brash, fast-talking New York City taxi driver and one of the central comic female leads in the musical "On the Town."
-
D.
Mildred Natwick
Mildred Natwick was an American character actress known for her versatile performances in film, theater, and television, often in witty or eccentric supporting roles.
-
E.
Lucille Sheardown
Lucille Sheardown was one of the later wives of American inventor Lee de Forest, associated with his personal life rather than his pioneering work in radio and electronics.
- 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.