Triple
T12809826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe (1970 film) |
E306240
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Melissa Compton
Melissa Compton is a character in the 1970 drama film "Joe," which explores generational conflict and social tensions in late-1960s America.
|
E1015190
|
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: Melissa Compton | Statement: [Joe (1970 film), featuresCharacter, Melissa Compton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa Compton Context triple: [Joe (1970 film), featuresCharacter, Melissa Compton]
-
A.
Emily Greer
Emily Greer is a notable individual recognized as a prominent bearer of the surname Greer.
-
B.
Kate Burroughs
Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
-
C.
Kate Healey
Kate Healey is a notable individual recognized as a prominent bearer of the Healey surname.
-
D.
Melanie Reeve
Melanie Reeve is the wife of American filmmaker Matt Reeves, known for her long-term partnership with the director behind films like Cloverfield and The Batman.
-
E.
Pamela Addison
Pamela Addison is known as the wife of John Addison.
- 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: Melissa Compton Triple: [Joe (1970 film), featuresCharacter, Melissa Compton]
Generated description
Melissa Compton is a character in the 1970 drama film "Joe," which explores generational conflict and social tensions in late-1960s America.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Melissa Compton Target entity description: Melissa Compton is a character in the 1970 drama film "Joe," which explores generational conflict and social tensions in late-1960s America.
-
A.
Emily Greer
Emily Greer is a notable individual recognized as a prominent bearer of the surname Greer.
-
B.
Kate Burroughs
Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
-
C.
Kate Healey
Kate Healey is a notable individual recognized as a prominent bearer of the Healey surname.
-
D.
Melanie Reeve
Melanie Reeve is the wife of American filmmaker Matt Reeves, known for her long-term partnership with the director behind films like Cloverfield and The Batman.
-
E.
Pamela Addison
Pamela Addison is known as the wife of John Addison.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e817598819080fdd61e9d61236e |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0e0e90881908f6e523754107e75 |
completed | May 3, 2026, 3:28 a.m. |
| NEDg | Description generation | batch_69f6c277e6248190870b3bf9869716a7 |
completed | May 3, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c38bc0b08190b76cb0853d99ad82 |
completed | May 3, 2026, 3:39 a.m. |
Created at: April 9, 2026, 5:31 p.m.