Triple
T12167043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terri Windling |
E289859
|
entity |
| Predicate | coEditorWith |
P8375
|
FINISHED |
| Object |
Ellen Datlow
Ellen Datlow is an acclaimed American editor best known for her influential work in horror, fantasy, and science fiction anthologies.
|
E966672
|
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: Ellen Datlow | Statement: [Terri Windling, coEditorWith, Ellen Datlow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellen Datlow Context triple: [Terri Windling, coEditorWith, Ellen Datlow]
-
A.
Ellen Bowen
Ellen Bowen is a fictional character from the 1951 MGM musical film "Royal Wedding," which starred Fred Astaire.
-
B.
Ellen Bowen
Ellen Bowen is a woman known primarily as the sister of Tom Bowen, the Australian manual therapist who founded the Bowen technique.
-
C.
Ellen Thomas
Ellen Thomas is a British actress known for her work in television, film, and theatre, including prominent roles in UK dramas and comedies.
-
D.
Lenore Kipp
Lenore Kipp was the wife of American actor Joseph Cotten, known primarily for her long marriage to the classic Hollywood star.
-
E.
Maria Ewing
Maria Ewing was an acclaimed American opera singer and actress known for her intense dramatic presence and versatile mezzo-soprano and soprano roles on major international stages.
- 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: Ellen Datlow Triple: [Terri Windling, coEditorWith, Ellen Datlow]
Generated description
Ellen Datlow is an acclaimed American editor best known for her influential work in horror, fantasy, and science fiction anthologies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ellen Datlow Target entity description: Ellen Datlow is an acclaimed American editor best known for her influential work in horror, fantasy, and science fiction anthologies.
-
A.
Ellen Bowen
Ellen Bowen is a fictional character from the 1951 MGM musical film "Royal Wedding," which starred Fred Astaire.
-
B.
Ellen Bowen
Ellen Bowen is a woman known primarily as the sister of Tom Bowen, the Australian manual therapist who founded the Bowen technique.
-
C.
Ellen Thomas
Ellen Thomas is a British actress known for her work in television, film, and theatre, including prominent roles in UK dramas and comedies.
-
D.
Lenore Kipp
Lenore Kipp was the wife of American actor Joseph Cotten, known primarily for her long marriage to the classic Hollywood star.
-
E.
Maria Ewing
Maria Ewing was an acclaimed American opera singer and actress known for her intense dramatic presence and versatile mezzo-soprano and soprano roles on major international stages.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d85c088190a74fb7590877659b |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6a2716081909620a9d11cfcc2d8 |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f6018043f48190a3062de4e0d4a3f5 |
completed | May 2, 2026, 1:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60232d89881909f254da6deb7f321 |
completed | May 2, 2026, 1:54 p.m. |
Created at: April 8, 2026, 9:50 p.m.