Triple
T7809600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Movie Crazy |
E180643
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Harold Hall
Harold Hall is the bumbling yet endearing aspiring performer portrayed by Harold Lloyd in the 1932 comedy film "Movie Crazy."
|
E694555
|
NE FINISHED |
How this triple was built (4 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: Harold Hall | Statement: [Movie Crazy, mainCharacter, Harold Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harold Hall Context triple: [Movie Crazy, mainCharacter, Harold Hall]
-
A.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
-
B.
Paul Hall
Paul Hall is a film producer best known for his work on major studio projects, including the 2000 action-crime film "Shaft."
-
C.
Henry Halls
Henry Halls is one of the children of American actor Matt Bomer and his husband, publicist Simon Halls.
-
D.
Randolph Hill
Randolph Hill is a small residential and scenic area within the town of Randolph, New Hampshire, known for its rural character and proximity to the White Mountains.
-
E.
Simon Hall
Simon Hall is a primary academic and administrative building at Washington University's Olin Business School that houses classrooms, offices, and student facilities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Harold Hall Triple: [Movie Crazy, mainCharacter, Harold Hall]
Generated description
Harold Hall is the bumbling yet endearing aspiring performer portrayed by Harold Lloyd in the 1932 comedy film "Movie Crazy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harold Hall Target entity description: Harold Hall is the bumbling yet endearing aspiring performer portrayed by Harold Lloyd in the 1932 comedy film "Movie Crazy."
-
A.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
-
B.
Paul Hall
Paul Hall is a film producer best known for his work on major studio projects, including the 2000 action-crime film "Shaft."
-
C.
Henry Halls
Henry Halls is one of the children of American actor Matt Bomer and his husband, publicist Simon Halls.
-
D.
Randolph Hill
Randolph Hill is a small residential and scenic area within the town of Randolph, New Hampshire, known for its rural character and proximity to the White Mountains.
-
E.
Simon Hall
Simon Hall is a primary academic and administrative building at Washington University's Olin Business School that houses classrooms, offices, and student facilities.
- F. None of above. chosen
Provenance (5 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78bb4b08190b2b3b51c5a0a033c |
completed | March 30, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb145b93788190a89f26dacbd0b437 |
completed | March 31, 2026, 12:24 a.m. |
| NEDg | Description generation | batch_69cb173190a88190b31fd7973bc19d43 |
completed | March 31, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a56d25881908b8413b82edf5508 |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:37 p.m.