Triple
T3760323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Princess Bride |
E82144
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Buttercup
Buttercup is the strong-willed yet romantic heroine of the fantasy adventure story "The Princess Bride," known for her enduring love for Westley.
|
E385782
|
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: Buttercup | Statement: [The Princess Bride, mainCharacter, Buttercup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buttercup Context triple: [The Princess Bride, mainCharacter, Buttercup]
-
A.
Daisy Dove Bloom
Daisy Dove Bloom is the daughter of American singer Katy Perry and English actor Orlando Bloom, born in 2020.
-
B.
June Star
June Star is a bratty, outspoken young girl in Flannery O’Connor’s short story “A Good Man Is Hard to Find,” known for her rudeness and lack of empathy.
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
-
E.
Sabrina
Sabrina is a classic 1954 romantic comedy film directed by Billy Wilder, starring Audrey Hepburn, Humphrey Bogart, and William Holden in a Cinderella-like tale of love and transformation.
- 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: Buttercup Triple: [The Princess Bride, mainCharacter, Buttercup]
Generated description
Buttercup is the strong-willed yet romantic heroine of the fantasy adventure story "The Princess Bride," known for her enduring love for Westley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Buttercup Target entity description: Buttercup is the strong-willed yet romantic heroine of the fantasy adventure story "The Princess Bride," known for her enduring love for Westley.
-
A.
Daisy Dove Bloom
Daisy Dove Bloom is the daughter of American singer Katy Perry and English actor Orlando Bloom, born in 2020.
-
B.
June Star
June Star is a bratty, outspoken young girl in Flannery O’Connor’s short story “A Good Man Is Hard to Find,” known for her rudeness and lack of empathy.
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
-
E.
Sabrina
Sabrina is a classic 1954 romantic comedy film directed by Billy Wilder, starring Audrey Hepburn, Humphrey Bogart, and William Holden in a Cinderella-like tale of love and transformation.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc3d3f48190974cec104080949f |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5172abc81909cfa709ea866dc57 |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e65f868c819099b4fbf129773e6d |
completed | March 14, 2026, 4:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e6bc95cc8190852b833e111cd889 |
completed | March 14, 2026, 4:40 a.m. |
Created at: March 8, 2026, 3:35 p.m.