Triple
T13153918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toni Marilyn Smith |
E312533
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object |
Marilyn
Marilyn is the middle name of Toni Marilyn Smith.
|
E1023978
|
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: Marilyn | Statement: [Toni Marilyn Smith, middleName, Marilyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marilyn Context triple: [Toni Marilyn Smith, middleName, Marilyn]
-
A.
Marilyn
A Marilyn is a type of British hill or mountain classified by having a prominence of at least 150 meters, regardless of its absolute height.
-
B.
Marilyn
Marilyn is the given first name of American country music singer Jeannie Seely.
-
C.
Marlene
Marlene is an energetic and friendly otter who appears as a main supporting character in the animated series "The Penguins of Madagascar."
-
D.
Marlene
Marlene is a German biographical film directed by Joseph Vilsmaier about the life and career of actress and singer Marlene Dietrich.
-
E.
Marilyn Monroe
Marilyn Monroe was an iconic American actress, model, and sex symbol of the mid-20th century, renowned for her comedic roles, glamorous image, and enduring cultural legacy.
- 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: Marilyn Triple: [Toni Marilyn Smith, middleName, Marilyn]
Generated description
Marilyn is the middle name of Toni Marilyn Smith.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marilyn Target entity description: Marilyn is the middle name of Toni Marilyn Smith.
-
A.
Marilyn
A Marilyn is a type of British hill or mountain classified by having a prominence of at least 150 meters, regardless of its absolute height.
-
B.
Marilyn
Marilyn is the given first name of American country music singer Jeannie Seely.
-
C.
Marlene
Marlene is a German biographical film directed by Joseph Vilsmaier about the life and career of actress and singer Marlene Dietrich.
-
D.
Marlene
Marlene is an energetic and friendly otter who appears as a main supporting character in the animated series "The Penguins of Madagascar."
-
E.
Marilyn Monroe
Marilyn Monroe was an iconic American actress, model, and sex symbol of the mid-20th century, renowned for her comedic roles, glamorous image, and enduring cultural legacy.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bd317e0819086e383f8e4583630 |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaee8aa0819089994b85d56c7740 |
completed | May 3, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69f6ef102fb08190b8a9646e5b45155c |
completed | May 3, 2026, 6:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ef933f888190880e680f7f4c1c29 |
completed | May 3, 2026, 6:47 a.m. |
Created at: April 9, 2026, 9:11 p.m.