Triple
T945275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christy Mathewson |
E20397
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Matty
Matty is the famous nickname of Christy Mathewson, one of early baseball’s greatest pitchers and a Hall of Famer for the New York Giants.
|
E111113
|
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: Matty | Statement: [Christy Mathewson, nickname, Matty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matty Context triple: [Christy Mathewson, nickname, Matty]
-
A.
Myles
Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
-
B.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
C.
Gavin
Gavin is a masculine given name of Celtic origin, commonly used in English-speaking countries.
-
D.
Owen
Owen is a common Welsh-origin surname borne by many people, including the renowned World War I poet Wilfred Owen.
-
E.
Marty
Marty is a 1955 American romantic drama film that won the Academy Award for Best Picture and is renowned for its poignant portrayal of a lonely butcher’s search for love.
- 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: Matty Triple: [Christy Mathewson, nickname, Matty]
Generated description
Matty is the famous nickname of Christy Mathewson, one of early baseball’s greatest pitchers and a Hall of Famer for the New York Giants.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matty Target entity description: Matty is the famous nickname of Christy Mathewson, one of early baseball’s greatest pitchers and a Hall of Famer for the New York Giants.
-
A.
Myles
Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
-
B.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
C.
Gavin
Gavin is a masculine given name of Celtic origin, commonly used in English-speaking countries.
-
D.
Owen
Owen is a common Welsh-origin surname borne by many people, including the renowned World War I poet Wilfred Owen.
-
E.
Marty
Marty is a 1955 American romantic drama film that won the Academy Award for Best Picture and is renowned for its poignant portrayal of a lonely butcher’s search for love.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a61b648190b1b6c932e047e161 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826e7d55c8190b9b871caead76733 |
completed | March 4, 2026, 12:34 p.m. |
| NEDg | Description generation | batch_69a845a793e08190892fe1a545095f62 |
completed | March 4, 2026, 2:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a8463631608190a9ada5605e9625aa |
completed | March 4, 2026, 2:48 p.m. |
Created at: March 1, 2026, 7:40 p.m.