Triple
T4030039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Wong in Chinatown |
E83685
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Roberta Logan
Roberta Logan is a fictional character appearing in the mystery film "Mr. Wong in Chinatown."
|
E412463
|
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: Roberta Logan | Statement: [Mr. Wong in Chinatown, character, Roberta Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberta Logan Context triple: [Mr. Wong in Chinatown, character, Roberta Logan]
-
A.
Jacqueline Logan
Jacqueline Logan was an American silent film actress best known for her prominent roles in 1920s Hollywood cinema.
-
B.
Katherine Rogers
Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
-
C.
Lindy Robbins
Lindy Robbins is an American songwriter known for crafting hit pop songs for major artists across the contemporary music industry.
-
D.
Sheila Kelley
Sheila Kelley is an American actress and dancer best known for her roles in film and television and for founding the S Factor pole-dance fitness movement.
-
E.
Rosemary Woodruff
Rosemary Woodruff was an American counterculture figure and activist best known for her involvement in the 1960s psychedelic movement alongside Timothy Leary.
- 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: Roberta Logan Triple: [Mr. Wong in Chinatown, character, Roberta Logan]
Generated description
Roberta Logan is a fictional character appearing in the mystery film "Mr. Wong in Chinatown."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roberta Logan Target entity description: Roberta Logan is a fictional character appearing in the mystery film "Mr. Wong in Chinatown."
-
A.
Jacqueline Logan
Jacqueline Logan was an American silent film actress best known for her prominent roles in 1920s Hollywood cinema.
-
B.
Katherine Rogers
Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
-
C.
Lindy Robbins
Lindy Robbins is an American songwriter known for crafting hit pop songs for major artists across the contemporary music industry.
-
D.
Sheila Kelley
Sheila Kelley is an American actress and dancer best known for her roles in film and television and for founding the S Factor pole-dance fitness movement.
-
E.
Rosemary Woodruff
Rosemary Woodruff was an American counterculture figure and activist best known for her involvement in the 1960s psychedelic movement alongside Timothy Leary.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaf1d8208190951a20ad7e5ab7bc |
completed | March 9, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b4a54c48190ae8abe0188b9738b |
completed | March 14, 2026, 2:06 p.m. |
| NEDg | Description generation | batch_69b56c4c41c88190b00ab8fc43686afb |
completed | March 14, 2026, 2:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b56cc2ae948190a5e13992626dd547 |
completed | March 14, 2026, 2:12 p.m. |
Created at: March 9, 2026, 3:36 p.m.