Triple
T14292920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mattye |
E354360
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Matty |
E354360
|
NE FINISHED |
How this triple was built (2 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: [Mattye, relatedName, Matty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matty Context triple: [Mattye, relatedName, Matty]
-
A.
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.
-
B.
Matty
Matty is a common diminutive or nickname for the given name Matthew.
-
C.
Mattye
chosen
Mattye is a feminine given name derived from the masculine name Matthew.
-
D.
Myles
Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
-
E.
Matt
Matt is the given name of Matt Eberflus, an American football coach best known as the head coach of the Chicago Bears in the NFL.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de7179368081908117a9ccfbf94fd4 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5504dc6c8190a4d8a5985632901d |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:11 a.m.