Triple
T14467455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Mulaney |
E358749
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Anna Marie Tendler
Anna Marie Tendler is an American multimedia artist, author, and hairstylist known for her work in makeup and textile art as well as her former marriage to comedian John Mulaney.
|
E1122362
|
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: Anna Marie Tendler | Statement: [John Mulaney, spouse, Anna Marie Tendler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Marie Tendler Context triple: [John Mulaney, spouse, Anna Marie Tendler]
-
A.
Annmarie Fulton
Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
-
B.
Ann Lembeck
Ann Lembeck is the wife of American actor and comedian Denis Leary.
-
C.
Karen Truesdell
Karen Truesdell is best known as the first wife of acclaimed American actor George C. Scott.
-
D.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
-
E.
Linda Nordley
Linda Nordley is a central female character in the 1953 adventure film "Mogambo," portrayed as a refined Englishwoman whose arrival complicates the romantic and emotional dynamics on an African safari.
- 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: Anna Marie Tendler Triple: [John Mulaney, spouse, Anna Marie Tendler]
Generated description
Anna Marie Tendler is an American multimedia artist, author, and hairstylist known for her work in makeup and textile art as well as her former marriage to comedian John Mulaney.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anna Marie Tendler Target entity description: Anna Marie Tendler is an American multimedia artist, author, and hairstylist known for her work in makeup and textile art as well as her former marriage to comedian John Mulaney.
-
A.
Annmarie Fulton
Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
-
B.
Ann Lembeck
Ann Lembeck is the wife of American actor and comedian Denis Leary.
-
C.
Karen Truesdell
Karen Truesdell is best known as the first wife of acclaimed American actor George C. Scott.
-
D.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
-
E.
Linda Nordley
Linda Nordley is a central female character in the 1953 adventure film "Mogambo," portrayed as a refined Englishwoman whose arrival complicates the romantic and emotional dynamics on an African safari.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f8613c819080424104c0b7f4c3 |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe3880ee4081908e783231de226448 |
completed | May 8, 2026, 7:24 p.m. |
| NEDg | Description generation | batch_69fe4687c6788190bf1785730ba48c87 |
completed | May 8, 2026, 8:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe47220a7481908543dc77afd2743a |
completed | May 8, 2026, 8:27 p.m. |
Created at: April 10, 2026, 1:19 a.m.