Triple
T984844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Room |
E21255
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Julia Bloch
Julia Bloch is an American poet, editor, and scholar known for her innovative work in contemporary poetry and literary criticism.
|
E211230
|
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: Julia Bloch | Statement: [Green Room, editedBy, Julia Bloch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julia Bloch Context triple: [Green Room, editedBy, Julia Bloch]
-
A.
Tatiana Schlossberg
Tatiana Schlossberg is an American journalist and author, known for her environmental reporting and as a member of the Kennedy family.
-
B.
Julia Cumson
Julia Cumson is a central fictional character in the 1980s American prime-time soap opera "Falcon Crest," known for her complex family ties and dramatic storylines within the powerful Channing dynasty.
-
C.
Nina Bernstein
Nina Bernstein is the daughter of renowned American composer and conductor Leonard Bernstein, known for helping preserve and promote her father's musical legacy.
-
D.
Alexandra Yatsko
Alexandra Yatsko is a film producer known for her work on the documentary "Love, Antosha."
-
E.
Julia Barfield
Julia Barfield is a British architect best known as the co-designer of the iconic London Eye observation wheel in London.
- 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: Julia Bloch Triple: [Green Room, editedBy, Julia Bloch]
Generated description
Julia Bloch is an American poet, editor, and scholar known for her innovative work in contemporary poetry and literary criticism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Julia Bloch Target entity description: Julia Bloch is an American poet, editor, and scholar known for her innovative work in contemporary poetry and literary criticism.
-
A.
Tatiana Schlossberg
Tatiana Schlossberg is an American journalist and author, known for her environmental reporting and as a member of the Kennedy family.
-
B.
Julia Cumson
Julia Cumson is a central fictional character in the 1980s American prime-time soap opera "Falcon Crest," known for her complex family ties and dramatic storylines within the powerful Channing dynasty.
-
C.
Nina Bernstein
Nina Bernstein is the daughter of renowned American composer and conductor Leonard Bernstein, known for helping preserve and promote her father's musical legacy.
-
D.
Alexandra Yatsko
Alexandra Yatsko is a film producer known for her work on the documentary "Love, Antosha."
-
E.
Julia Barfield
Julia Barfield is a British architect best known as the co-designer of the iconic London Eye observation wheel in London.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeab2f888819093d2b3e49b105802 |
completed | March 8, 2026, 9:31 p.m. |
| NEDg | Description generation | batch_69adeb330fe0819096ac927838b6ee2f |
completed | March 8, 2026, 9:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adebb1d7748190b5cd33d163368eae |
completed | March 8, 2026, 9:35 p.m. |
Created at: March 1, 2026, 7:41 p.m.