Triple
T28136546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliver Twist (1948 film) |
E714220
|
entity |
| Predicate | characterPortrayedByMaryClare |
P1507
|
FINISHED |
| Object |
Mrs. Corney
Mrs. Corney is the domineering and self-serving matron of the workhouse in Charles Dickens' novel "Oliver Twist."
|
E1806321
|
NE FINISHED |
How this triple was built (3 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: Mrs. Corney | Statement: [Oliver Twist (1948 film), characterPortrayedByMaryClare, Mrs. Corney]
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: Mrs. Corney Triple: [Oliver Twist (1948 film), characterPortrayedByMaryClare, Mrs. Corney]
Generated description
Mrs. Corney is the domineering and self-serving matron of the workhouse in Charles Dickens' novel "Oliver Twist."
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPortrayedByMaryClare Context triple: [Oliver Twist (1948 film), characterPortrayedByMaryClare, Mrs. Corney]
-
A.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
B.
motherPortrayedBy
Indicates that a person’s mother is depicted or played by a particular actor or performer.
-
C.
characterPlayedByKathleenQuinlan
Indicates that a given character is portrayed or acted by Kathleen Quinlan.
-
D.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
E.
sonCharacterPortrayedBy
Indicates that a person is the actor who portrays a specific son character in a work of fiction.
- F. None of above.
Provenance (6 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_69efd6af156c81908f50c2cd7db0e1ef |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a15d7a0277481908cd8f2f1b93059cf |
completed | May 26, 2026, 5:25 p.m. |
| NEDg | Description generation | batch_6a15da65e3f481909bcb009caacb671f |
completed | May 26, 2026, 5:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a15dda803a88190acf72fda12446639 |
completed | May 26, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 27, 2026, 9:50 p.m.