Triple
T14932085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Waldo |
E372291
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Waldo
Waldo is a surname of English origin borne by various notable individuals, including figures in American colonial and political history.
|
E1126863
|
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: Waldo | Statement: [Samuel Waldo, familyName, Waldo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waldo Context triple: [Samuel Waldo, familyName, Waldo]
-
A.
Waldo
Waldo is Mr. Magoo’s good-natured but often exasperated nephew who frequently appears in the classic Mr. Magoo animated cartoons.
-
B.
Waldo the Warrior
Waldo the Warrior is the athletic mascot representing Wisconsin Lutheran College, typically depicted as a spirited warrior figure embodying the school’s competitive and Christian values.
-
C.
The Ralph
The Ralph is a popular nickname for Highmark Stadium, the home field of the NFL’s Buffalo Bills in Orchard Park, New York.
-
D.
Wiarton Willie
Wiarton Willie is a famous Canadian groundhog celebrated for his annual Groundhog Day weather prediction festival in Wiarton, Ontario.
-
E.
King Wally
King Wally is the legendary Australian rugby league playmaker Wally Lewis, renowned as one of the greatest players in the sport’s history.
- 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: Waldo Triple: [Samuel Waldo, familyName, Waldo]
Generated description
Waldo is a surname of English origin borne by various notable individuals, including figures in American colonial and political history.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Waldo Target entity description: Waldo is a surname of English origin borne by various notable individuals, including figures in American colonial and political history.
-
A.
Waldo
Waldo is Mr. Magoo’s good-natured but often exasperated nephew who frequently appears in the classic Mr. Magoo animated cartoons.
-
B.
Waldo the Warrior
Waldo the Warrior is the athletic mascot representing Wisconsin Lutheran College, typically depicted as a spirited warrior figure embodying the school’s competitive and Christian values.
-
C.
The Ralph
The Ralph is a popular nickname for Highmark Stadium, the home field of the NFL’s Buffalo Bills in Orchard Park, New York.
-
D.
Wiarton Willie
Wiarton Willie is a famous Canadian groundhog celebrated for his annual Groundhog Day weather prediction festival in Wiarton, Ontario.
-
E.
King Wally
King Wally is the legendary Australian rugby league playmaker Wally Lewis, renowned as one of the greatest players in the sport’s history.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64550dc8190ba44120df00ba498 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72c86b5c81909e601a3fc78276bd |
completed | May 8, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69fe7360c11481908e2e5127b466e31b |
completed | May 8, 2026, 11:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe743c37308190a045ef5f0ade8508 |
completed | May 8, 2026, 11:39 p.m. |
Created at: April 10, 2026, 2:36 a.m.