Triple
T16371301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let’s Get Lost |
E397569
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Ruth Young
Ruth Young is an actress known for her role in the jazz documentary film "Let’s Get Lost."
|
E1212159
|
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: Ruth Young | Statement: [Let’s Get Lost, hasCastMember, Ruth Young]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruth Young Context triple: [Let’s Get Lost, hasCastMember, Ruth Young]
-
A.
Ruth Riley
Ruth Riley is a former American professional basketball center best known for starring at Notre Dame and winning WNBA championships and a Finals MVP award with the Detroit Shock.
-
B.
Ruth Cunningham
Ruth Cunningham was the wife of American colonial lawyer and patriot James Otis Jr., a prominent figure in the early resistance to British rule.
-
C.
Ruth Fisher
Ruth Fisher is a central character in the television drama "Six Feet Under," portrayed as the emotionally complex matriarch of the Fisher family who struggles with grief, identity, and independence.
-
D.
Margaret Hogan
Margaret Hogan was the wife of legendary Major League Baseball manager and team owner Connie Mack.
-
E.
Margaret Hayes
Margaret Hayes was an American film and television actress active in the mid-20th century, known for her supporting roles in dramas and crime films.
- 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: Ruth Young Triple: [Let’s Get Lost, hasCastMember, Ruth Young]
Generated description
Ruth Young is an actress known for her role in the jazz documentary film "Let’s Get Lost."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruth Young Target entity description: Ruth Young is an actress known for her role in the jazz documentary film "Let’s Get Lost."
-
A.
Ruth Riley
Ruth Riley is a former American professional basketball center best known for starring at Notre Dame and winning WNBA championships and a Finals MVP award with the Detroit Shock.
-
B.
Ruth Cunningham
Ruth Cunningham was the wife of American colonial lawyer and patriot James Otis Jr., a prominent figure in the early resistance to British rule.
-
C.
Ruth Fisher
Ruth Fisher is a central character in the television drama "Six Feet Under," portrayed as the emotionally complex matriarch of the Fisher family who struggles with grief, identity, and independence.
-
D.
Margaret Hogan
Margaret Hogan was the wife of legendary Major League Baseball manager and team owner Connie Mack.
-
E.
Margaret Hayes
Margaret Hayes was an American film and television actress active in the mid-20th century, known for her supporting roles in dramas and crime films.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff420d04819096ff12e08edf2f8b |
completed | April 18, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c522a7c8190a306b85354a087fd |
completed | May 10, 2026, 8:05 a.m. |
| NEDg | Description generation | batch_6a003e77677c81908687df4f9c1c1bb8 |
completed | May 10, 2026, 8:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a003f300e688190a12352fef2f801f9 |
completed | May 10, 2026, 8:17 a.m. |
Created at: April 10, 2026, 5:08 a.m.