Triple
T6161926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Getting Married |
E137461
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Abby Buchman
Abby Buchman is a central character in the drama film "Rachel Getting Married," around whom much of the story’s emotional tension and family dynamics revolve.
|
E574328
|
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: Abby Buchman | Statement: [Rachel Getting Married, mainCharacter, Abby Buchman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abby Buchman Context triple: [Rachel Getting Married, mainCharacter, Abby Buchman]
-
A.
Abby McGrew
Abby McGrew is an American philanthropist best known as the wife of former NFL quarterback Eli Manning.
-
B.
Abbie Steinhauser
Abbie Steinhauser is an architect known for her work on the design of the Van Abbemuseum.
-
C.
Abby Blodgett
Abby Blodgett is a person notable enough to be specifically cited as a bearer of the Blodgett surname.
-
D.
Abby Erceg
Abby Erceg is a New Zealand professional soccer defender and longtime national team captain known for her leadership and success in top women’s leagues, including the NWSL.
-
E.
Hannah Sullivan
Hannah Sullivan is a contemporary British poet and academic whose debut collection "Three Poems" won widespread acclaim for its innovative, formally adventurous exploration of modern life.
- 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: Abby Buchman Triple: [Rachel Getting Married, mainCharacter, Abby Buchman]
Generated description
Abby Buchman is a central character in the drama film "Rachel Getting Married," around whom much of the story’s emotional tension and family dynamics revolve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Abby Buchman Target entity description: Abby Buchman is a central character in the drama film "Rachel Getting Married," around whom much of the story’s emotional tension and family dynamics revolve.
-
A.
Abby McGrew
Abby McGrew is an American philanthropist best known as the wife of former NFL quarterback Eli Manning.
-
B.
Abbie Steinhauser
Abbie Steinhauser is an architect known for her work on the design of the Van Abbemuseum.
-
C.
Abby Blodgett
Abby Blodgett is a person notable enough to be specifically cited as a bearer of the Blodgett surname.
-
D.
Abby Erceg
Abby Erceg is a New Zealand professional soccer defender and longtime national team captain known for her leadership and success in top women’s leagues, including the NWSL.
-
E.
Hannah Sullivan
Hannah Sullivan is a contemporary British poet and academic whose debut collection "Three Poems" won widespread acclaim for its innovative, formally adventurous exploration of modern life.
- 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_69c008a54fc88190b6ce4416490ca79d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d371484819090c18b62b095b49e |
completed | March 22, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c14199f024819089af02b1c0eebfad |
completed | March 23, 2026, 1:35 p.m. |
| NEDg | Description generation | batch_69c1467ef4d48190b714823935318c0a |
completed | March 23, 2026, 1:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c146f59d9881908fdc6c0137f0ead7 |
completed | March 23, 2026, 1:58 p.m. |
Created at: March 22, 2026, 4:17 p.m.