Triple
T16702273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacKenzie Scott |
E405881
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Tuttle
Tuttle is the birth surname of MacKenzie Scott, the American novelist and philanthropist formerly married to Jeff Bezos.
|
E1228809
|
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: Tuttle | Statement: [MacKenzie Scott, familyName, Tuttle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tuttle Context triple: [MacKenzie Scott, familyName, Tuttle]
-
A.
Tani
Tani is a group of closely related Tibeto-Burman languages spoken primarily in the northeastern Indian states of Arunachal Pradesh and Assam.
-
B.
Tani
Tani is a Pashtun tribal group primarily associated with Afghanistan’s Khost region.
-
C.
Tani Tateki
Tani Tateki was a Japanese samurai and military commander of the Meiji era who played a key role in government forces during the Satsuma Rebellion.
-
D.
Tasuku
Tasuku is a Japanese given name most famously borne by immunologist Tasuku Honjo, a Nobel Prize laureate recognized for his work on cancer immunotherapy.
-
E.
Hoshi
Hoshi is a South Korean singer, dancer, and choreographer best known as the performance team leader of the K-pop boy group Seventeen.
- 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: Tuttle Triple: [MacKenzie Scott, familyName, Tuttle]
Generated description
Tuttle is the birth surname of MacKenzie Scott, the American novelist and philanthropist formerly married to Jeff Bezos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tuttle Target entity description: Tuttle is the birth surname of MacKenzie Scott, the American novelist and philanthropist formerly married to Jeff Bezos.
-
A.
Tani
Tani is a group of closely related Tibeto-Burman languages spoken primarily in the northeastern Indian states of Arunachal Pradesh and Assam.
-
B.
Tani
Tani is a Pashtun tribal group primarily associated with Afghanistan’s Khost region.
-
C.
Tani Tateki
Tani Tateki was a Japanese samurai and military commander of the Meiji era who played a key role in government forces during the Satsuma Rebellion.
-
D.
Tasuku
Tasuku is a Japanese given name most famously borne by immunologist Tasuku Honjo, a Nobel Prize laureate recognized for his work on cancer immunotherapy.
-
E.
Hoshi
Hoshi is a South Korean singer, dancer, and choreographer best known as the performance team leader of the K-pop boy group Seventeen.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383326d7081909ef4c3b724876513 |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0091a0dee08190a67ed5df2008c91e |
completed | May 10, 2026, 2:09 p.m. |
| NEDg | Description generation | batch_6a00923f1da08190b6b2c869284099bc |
completed | May 10, 2026, 2:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00931aa1d88190a0775e74779b3a6b |
completed | May 10, 2026, 2:15 p.m. |
Created at: April 10, 2026, 5:19 a.m.