Triple
T3136936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikki Haley |
E65553
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Michael Haley
Michael Haley is an American military officer and businessman best known as the husband of former South Carolina governor and U.N. ambassador Nikki Haley.
|
E329398
|
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: Michael Haley | Statement: [Nikki Haley, spouse, Michael Haley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Haley Context triple: [Nikki Haley, spouse, Michael Haley]
-
A.
Will Blackwell
Will Blackwell is a former American football wide receiver who played college football at San Diego State University before going on to play in the NFL.
-
B.
Surangel Whipps Jr.
Surangel Whipps Jr. is a Palauan politician and businessman who serves as the president of the Republic of Palau.
-
C.
Mr. Haley
Mr. Haley is a coarse, profit-driven slave trader in Harriet Beecher Stowe’s novel "Uncle Tom’s Cabin."
-
D.
Justice Smith
Justice Smith is an American actor known for roles in projects such as "The Get Down," "Jurassic World: Fallen Kingdom," and "Detective Pikachu."
-
E.
Ron Feemster
Ron Feemster is a music producer known for his work on the album "Afrodisiac."
- 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: Michael Haley Triple: [Nikki Haley, spouse, Michael Haley]
Generated description
Michael Haley is an American military officer and businessman best known as the husband of former South Carolina governor and U.N. ambassador Nikki Haley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Haley Target entity description: Michael Haley is an American military officer and businessman best known as the husband of former South Carolina governor and U.N. ambassador Nikki Haley.
-
A.
Will Blackwell
Will Blackwell is a former American football wide receiver who played college football at San Diego State University before going on to play in the NFL.
-
B.
Surangel Whipps Jr.
Surangel Whipps Jr. is a Palauan politician and businessman who serves as the president of the Republic of Palau.
-
C.
Mr. Haley
Mr. Haley is a coarse, profit-driven slave trader in Harriet Beecher Stowe’s novel "Uncle Tom’s Cabin."
-
D.
Justice Smith
Justice Smith is an American actor known for roles in projects such as "The Get Down," "Jurassic World: Fallen Kingdom," and "Detective Pikachu."
-
E.
Ron Feemster
Ron Feemster is a music producer known for his work on the album "Afrodisiac."
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada564eacc8190a54d07b4eb31c196 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f8a1a2081909081c36075d4ddbe |
completed | March 12, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b2137b30508190a5a9a439d77ae3bb |
completed | March 12, 2026, 1:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b21413338c8190997d0f2f11f41008 |
completed | March 12, 2026, 1:17 a.m. |
Created at: March 8, 2026, 3:05 p.m.