Triple
T19708538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Millett |
E473277
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Millett
Millett is an English surname most notably associated with Lord Millett, a distinguished British judge and law lord.
|
E1391595
|
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: Millett | Statement: [Lord Millett, familyName, Millett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Millett Context triple: [Lord Millett, familyName, Millett]
-
A.
Trulaske
Trulaske is the commonly used name for the Robert J. Trulaske, Sr. College of Business at the University of Missouri, a business school offering undergraduate and graduate programs in fields such as accounting, finance, and management.
-
B.
Matta
Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
-
C.
Matta
Matta is a town located in Pakistan’s Swat District, known for its agricultural surroundings and scenic mountainous landscape.
-
D.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
-
E.
Cunlhat
Cunlhat is a small rural commune in central France’s Puy-de-Dôme department, known for its traditional Auvergne countryside setting.
- 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: Millett Triple: [Lord Millett, familyName, Millett]
Generated description
Millett is an English surname most notably associated with Lord Millett, a distinguished British judge and law lord.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Millett Target entity description: Millett is an English surname most notably associated with Lord Millett, a distinguished British judge and law lord.
-
A.
Trulaske
Trulaske is the commonly used name for the Robert J. Trulaske, Sr. College of Business at the University of Missouri, a business school offering undergraduate and graduate programs in fields such as accounting, finance, and management.
-
B.
Matta
Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
-
C.
Matta
Matta is a town located in Pakistan’s Swat District, known for its agricultural surroundings and scenic mountainous landscape.
-
D.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
-
E.
Cunlhat
Cunlhat is a small rural commune in central France’s Puy-de-Dôme department, known for its traditional Auvergne countryside setting.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642bc754481908bdf5bfad069aec8 |
completed | April 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ab9cbf0c8190a34ceeeb9960677b |
completed | May 15, 2026, 11:26 p.m. |
| NEDg | Description generation | batch_6a07ac51fddc8190840698fb5cee0ea0 |
completed | May 15, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ae6493608190b8bc885ab8a916b2 |
completed | May 15, 2026, 11:38 p.m. |
Created at: April 10, 2026, 1:46 p.m.