Triple
T10812896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suellen O'Hara |
E255146
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Suellen
Suellen is a feminine given name, best known from the character Suellen O'Hara in Margaret Mitchell's novel "Gone with the Wind."
|
E887491
|
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: Suellen | Statement: [Suellen O'Hara, givenName, Suellen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suellen Context triple: [Suellen O'Hara, givenName, Suellen]
-
A.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
-
B.
Suzanne
Suzanne is a feminine given name of French origin, derived from the Hebrew name Shoshannah meaning “lily.”
-
C.
Suzanne
Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
-
D.
Susannah
Susannah is one of the central, romantically entangled characters in Alan Ayckbourn’s comedic stage play "Bedroom Farce."
-
E.
Glennis
Glennis is a feminine given name, best known for belonging to Glennis Dickhouse Yeager, the wife of test pilot Chuck Yeager and namesake of the Bell X-1 aircraft "Glamorous Glennis."
- 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: Suellen Triple: [Suellen O'Hara, givenName, Suellen]
Generated description
Suellen is a feminine given name, best known from the character Suellen O'Hara in Margaret Mitchell's novel "Gone with the Wind."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suellen Target entity description: Suellen is a feminine given name, best known from the character Suellen O'Hara in Margaret Mitchell's novel "Gone with the Wind."
-
A.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
-
B.
Suzanne
Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
-
C.
Suzanne
Suzanne is a feminine given name of French origin, derived from the Hebrew name Shoshannah meaning “lily.”
-
D.
Susannah
Susannah is one of the central, romantically entangled characters in Alan Ayckbourn’s comedic stage play "Bedroom Farce."
-
E.
Glennis
Glennis is a feminine given name, best known for belonging to Glennis Dickhouse Yeager, the wife of test pilot Chuck Yeager and namesake of the Bell X-1 aircraft "Glamorous Glennis."
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733eadda48190b2b1183ee60102cb |
completed | April 9, 2026, 5:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de853692f08190914cbeaf1a558730 |
completed | April 14, 2026, 6:19 p.m. |
| NEDg | Description generation | batch_69de8955b9d8819086ff98efbff6c7a0 |
completed | April 14, 2026, 6:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de8f4a318c819086559fd53506ab29 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 8, 2026, 9:18 p.m.