Triple
T19416185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beachcomber |
E485721
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Jean Barker
Jean Barker is a journalist best known for serving as editor of the publication *The Beachcomber*.
|
E1374936
|
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: Jean Barker | Statement: [The Beachcomber, editor, Jean Barker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean Barker Context triple: [The Beachcomber, editor, Jean Barker]
-
A.
Mary Pratt
Mary Pratt was a prominent Canadian realist painter renowned for her luminous, intimate depictions of everyday domestic scenes.
-
B.
Mary Bowne
Mary Bowne was a colonial-era New Yorker known primarily as the daughter of Quaker pioneer and religious freedom advocate John Bowne.
-
C.
Johanna Barker
Johanna Barker is the innocent and sheltered daughter of Sweeney Todd in the 2007 film adaptation of the musical thriller, serving as a central figure in the story’s themes of lost family and doomed romance.
-
D.
Sarah Ballard
Sarah Ballard was the mother of renowned Victorian-era Shakespearean actress Ellen Terry.
-
E.
Deborah Gist
Deborah Gist is an American education leader best known for serving as Rhode Island’s Commissioner of Elementary and Secondary Education and later as superintendent of Tulsa Public Schools.
- 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: Jean Barker Triple: [The Beachcomber, editor, Jean Barker]
Generated description
Jean Barker is a journalist best known for serving as editor of the publication *The Beachcomber*.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jean Barker Target entity description: Jean Barker is a journalist best known for serving as editor of the publication *The Beachcomber*.
-
A.
Mary Pratt
Mary Pratt was a prominent Canadian realist painter renowned for her luminous, intimate depictions of everyday domestic scenes.
-
B.
Mary Bowne
Mary Bowne was a colonial-era New Yorker known primarily as the daughter of Quaker pioneer and religious freedom advocate John Bowne.
-
C.
Johanna Barker
Johanna Barker is the innocent and sheltered daughter of Sweeney Todd in the 2007 film adaptation of the musical thriller, serving as a central figure in the story’s themes of lost family and doomed romance.
-
D.
Sarah Ballard
Sarah Ballard was the mother of renowned Victorian-era Shakespearean actress Ellen Terry.
-
E.
Deborah Gist
Deborah Gist is an American education leader best known for serving as Rhode Island’s Commissioner of Elementary and Secondary Education and later as superintendent of Tulsa Public Schools.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af9c8fc81909860de10b6720207 |
completed | April 20, 2026, 1:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0733ce2e6081909e8baebf638747f1 |
completed | May 15, 2026, 2:55 p.m. |
| NEDg | Description generation | batch_6a0734cfc2488190a488c40431a0b612 |
completed | May 15, 2026, 2:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0735c38b7881908489916ff2f2883e |
completed | May 15, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:37 p.m.