Triple
T13692758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RMM1 |
E328308
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object |
Harry Hendon
Harry Hendon is a software developer known for creating the RMM1 system.
|
E1054327
|
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: Harry Hendon | Statement: [RMM1, developedBy, Harry Hendon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Hendon Context triple: [RMM1, developedBy, Harry Hendon]
-
A.
Harry Henderson
Harry Henderson is a fictional character from the mid-20th-century American radio and television comedy series "Beulah," known for his role within the show's domestic household setting.
-
B.
Harry Rowlands
Harry Rowlands is known primarily as the husband of June Rowlands, the first female mayor of Toronto.
-
C.
Henry Scudder
Henry Scudder was a 17th-century English clergyman and devotional writer known for his influential Puritan work "The Christian's Daily Walk."
-
D.
Robert Henley
Robert Henley was a United States Navy officer honored for his service, for whom multiple U.S. Navy ships have been named.
-
E.
Paul Hunham
Paul Hunham is the curmudgeonly, intellectually rigorous boarding school teacher at the center of the film "The Holdovers," whose unlikely bond with a troubled student drives the story.
- 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: Harry Hendon Triple: [RMM1, developedBy, Harry Hendon]
Generated description
Harry Hendon is a software developer known for creating the RMM1 system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harry Hendon Target entity description: Harry Hendon is a software developer known for creating the RMM1 system.
-
A.
Harry Henderson
Harry Henderson is a fictional character from the mid-20th-century American radio and television comedy series "Beulah," known for his role within the show's domestic household setting.
-
B.
Harry Rowlands
Harry Rowlands is known primarily as the husband of June Rowlands, the first female mayor of Toronto.
-
C.
Henry Scudder
Henry Scudder was a 17th-century English clergyman and devotional writer known for his influential Puritan work "The Christian's Daily Walk."
-
D.
Robert Henley
Robert Henley was a United States Navy officer honored for his service, for whom multiple U.S. Navy ships have been named.
-
E.
Paul Hunham
Paul Hunham is the curmudgeonly, intellectually rigorous boarding school teacher at the center of the film "The Holdovers," whose unlikely bond with a troubled student drives the story.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8757b648190a26181efbad09a43 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944e7ea0819098a9fbf8842d314b |
completed | May 3, 2026, 6:30 p.m. |
| NEDg | Description generation | batch_69f79715571081909c1177a3fd09b4d5 |
completed | May 3, 2026, 6:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f797caabfc8190844e6b7d8125aeb6 |
completed | May 3, 2026, 6:45 p.m. |
Created at: April 9, 2026, 9:53 p.m.