Triple
T6679195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Thome |
E151934
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Thome
Thome is a surname most prominently associated with Jim Thome, a Hall of Fame American baseball slugger known for his power hitting.
|
E611639
|
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: Thome | Statement: [Jim Thome, familyName, Thome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thome Context triple: [Jim Thome, familyName, Thome]
-
A.
Jake Hoyt
Jake Hoyt is a rookie LAPD narcotics officer whose moral integrity is tested during a tumultuous day under a corrupt veteran detective in the film "Training Day."
-
B.
Seguin
Seguin is a small historic city in south-central Texas known for its pecan industry and preserved 19th-century architecture.
-
C.
Gwynn
Gwynn is the surname of Hall of Fame Major League Baseball right fielder Tony Gwynn, renowned for his exceptional hitting ability with the San Diego Padres.
-
D.
Doby
Doby is the surname of Larry Doby, the Hall of Fame baseball player who broke the American League color barrier.
-
E.
Lohse
Lohse is a German surname borne by various notable individuals in fields such as science, sports, and the arts.
- 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: Thome Triple: [Jim Thome, familyName, Thome]
Generated description
Thome is a surname most prominently associated with Jim Thome, a Hall of Fame American baseball slugger known for his power hitting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thome Target entity description: Thome is a surname most prominently associated with Jim Thome, a Hall of Fame American baseball slugger known for his power hitting.
-
A.
Jake Hoyt
Jake Hoyt is a rookie LAPD narcotics officer whose moral integrity is tested during a tumultuous day under a corrupt veteran detective in the film "Training Day."
-
B.
Seguin
Seguin is a small historic city in south-central Texas known for its pecan industry and preserved 19th-century architecture.
-
C.
Gwynn
Gwynn is the surname of Hall of Fame Major League Baseball right fielder Tony Gwynn, renowned for his exceptional hitting ability with the San Diego Padres.
-
D.
Doby
Doby is the surname of Larry Doby, the Hall of Fame baseball player who broke the American League color barrier.
-
E.
Lohse
Lohse is a German surname borne by various notable individuals in fields such as science, sports, and the arts.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0f6813c8190906f619b4276a232 |
completed | March 27, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7a9fda4819096d4bd3e8133cecb |
completed | March 27, 2026, 9:33 p.m. |
| NEDg | Description generation | batch_69c6f8b1e1f48190bc9058a8a21a4a62 |
completed | March 27, 2026, 9:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f9441d74819098f0639a29fdeb5e |
completed | March 27, 2026, 9:40 p.m. |
Created at: March 27, 2026, 2:03 p.m.