Triple
T10311583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendi McLendon-Covey |
E241902
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Wendi
Wendi is the first name of American actress and comedian Wendi McLendon-Covey, known for her roles in "Bridesmaids" and the TV series "The Goldbergs."
|
E855719
|
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: Wendi | Statement: [Wendi McLendon-Covey, givenName, Wendi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wendi Context triple: [Wendi McLendon-Covey, givenName, Wendi]
-
A.
Vickie
Vickie is the birth name of American model, actress, and television personality Anna Nicole Smith, who became famous as a Playboy Playmate and pop culture figure.
-
B.
Tina
Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
-
C.
Tina
Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
-
D.
Tina
Tina is a fictional character portrayed by American actress Idara Victor.
-
E.
Tina
Tina is a character portrayed by actress and comedian Melissa Rauch, known for her energetic and distinctive vocal performances.
- 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: Wendi Triple: [Wendi McLendon-Covey, givenName, Wendi]
Generated description
Wendi is the first name of American actress and comedian Wendi McLendon-Covey, known for her roles in "Bridesmaids" and the TV series "The Goldbergs."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wendi Target entity description: Wendi is the first name of American actress and comedian Wendi McLendon-Covey, known for her roles in "Bridesmaids" and the TV series "The Goldbergs."
-
A.
Vickie
Vickie is the birth name of American model, actress, and television personality Anna Nicole Smith, who became famous as a Playboy Playmate and pop culture figure.
-
B.
Tina
Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
-
C.
Tina
Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
-
D.
Tina
Tina is a fictional character portrayed by American actress Idara Victor.
-
E.
Tina
Tina is a feminine given name commonly used in English-speaking countries, often as a diminutive of names like Christina, Martina, or Valentina.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d32ac6c08190b23eb042b3ec284a |
completed | April 7, 2026, 9:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d78ece88190885768c979b038df |
completed | April 9, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_69d73186831481909555e2205d8783a7 |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d732bfc76c819089287477b54a7b77 |
completed | April 9, 2026, 5:01 a.m. |
Created at: April 6, 2026, 11:48 a.m.