Triple
T5267553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Dungy |
E118973
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Lauren Dungy
Lauren Dungy is an American author, educator, and philanthropist known for her work in foster care and adoption advocacy, as well as for co-authoring inspirational children's books.
|
E523921
|
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: Lauren Dungy | Statement: [Tony Dungy, spouse, Lauren Dungy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Dungy Context triple: [Tony Dungy, spouse, Lauren Dungy]
-
A.
Melissa Stribling
Melissa Stribling was a British actress best known for her role in the classic 1958 Hammer horror film "Horror of Dracula."
-
B.
Amy Eshleman
Amy Eshleman is an American former public librarian and education advocate best known as the wife of former Chicago mayor Lori Lightfoot.
-
C.
Amy Gilliam
Amy Gilliam is a film producer and the daughter of director Terry Gilliam, known for her work on projects such as the fantasy film "The Imaginarium of Doctor Parnassus."
-
D.
Molly Smith
Molly Smith is a daughter of FedEx founder and CEO Frederick W. Smith.
-
E.
Molly Smith
Molly Smith is an American film producer known for her work on acclaimed movies such as the crime thriller "Sicario."
- 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: Lauren Dungy Triple: [Tony Dungy, spouse, Lauren Dungy]
Generated description
Lauren Dungy is an American author, educator, and philanthropist known for her work in foster care and adoption advocacy, as well as for co-authoring inspirational children's books.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauren Dungy Target entity description: Lauren Dungy is an American author, educator, and philanthropist known for her work in foster care and adoption advocacy, as well as for co-authoring inspirational children's books.
-
A.
Melissa Stribling
Melissa Stribling was a British actress best known for her role in the classic 1958 Hammer horror film "Horror of Dracula."
-
B.
Amy Eshleman
Amy Eshleman is an American former public librarian and education advocate best known as the wife of former Chicago mayor Lori Lightfoot.
-
C.
Amy Gilliam
Amy Gilliam is a film producer and the daughter of director Terry Gilliam, known for her work on projects such as the fantasy film "The Imaginarium of Doctor Parnassus."
-
D.
Molly Smith
Molly Smith is a daughter of FedEx founder and CEO Frederick W. Smith.
-
E.
Molly Smith
Molly Smith is an American film producer known for her work on acclaimed movies such as the crime thriller "Sicario."
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bfc3f288190b128777caaad2275 |
completed | March 20, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf6c3bfdc48190984c8b55ece53fbe |
completed | March 22, 2026, 4:12 a.m. |
| NEDg | Description generation | batch_69bf6d267e808190b4085e07d31af1b7 |
completed | March 22, 2026, 4:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf6e497dd88190895fe68a7c8f6d65 |
completed | March 22, 2026, 4:21 a.m. |
Created at: March 20, 2026, 1:51 p.m.