Triple
T4875244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shawn Hochuli |
E109185
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Shawn |
E289134
|
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: Shawn | Statement: [Shawn Hochuli, givenName, Shawn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shawn Context triple: [Shawn Hochuli, givenName, Shawn]
-
A.
Shawn
chosen
Shawn is a given name, typically a variant of the name John or Sean, used primarily in English-speaking countries.
-
B.
Shawn Matthews
Shawn Matthews is a senior executive associated with the financial services firm Cantor Fitzgerald.
-
C.
Shaun
Shaun is a given name associated with the English actor Sean Bean, known for his roles in film and television such as "The Lord of the Rings" and "Game of Thrones."
-
D.
Shawn Hatosy
Shawn Hatosy is an American actor known for his roles in films like "Alpha Dog" and the TV series "Animal Kingdom."
-
E.
Evan Shelby
Evan Shelby was a colonial-era frontiersman and militia officer in the American South, best known as the father of Revolutionary War hero and Kentucky’s first governor, Isaac Shelby.
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6dba3efc8190adcf8b30490b4984 |
completed | March 20, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67f90e848190a36eee1e670657e4 |
completed | March 21, 2026, 9:42 a.m. |
Created at: March 20, 2026, 1:27 p.m.