Triple
T3589351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good |
E75987
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Andrew Good
Andrew Good is a former American Major League Baseball pitcher who played primarily for the Arizona Diamondbacks in the early 2000s.
|
E371668
|
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: Andrew Good | Statement: [Good, hasNotableBearer, Andrew Good]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Good Context triple: [Good, hasNotableBearer, Andrew Good]
-
A.
Jonathan Roberts
Jonathan Roberts is an American screenwriter best known for co-writing Disney’s animated classic "The Lion King."
-
B.
Douglas Guilfoyle
Douglas Guilfoyle is an international law scholar known for his work on the law of the sea, maritime security, and international criminal law.
-
C.
Chris Addison
Chris Addison is a British comedian, actor, writer, and director best known for his work on the political satire series "The Thick of It" and its film spin-off "In the Loop."
-
D.
Paul Givan
Paul Givan is a Democratic Unionist Party politician who served as First Minister of Northern Ireland.
-
E.
Paul Guilfoyle
Paul Guilfoyle is an American actor best known for playing Captain Jim Brass on the long-running television series CSI: Crime Scene Investigation.
- 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: Andrew Good Triple: [Good, hasNotableBearer, Andrew Good]
Generated description
Andrew Good is a former American Major League Baseball pitcher who played primarily for the Arizona Diamondbacks in the early 2000s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrew Good Target entity description: Andrew Good is a former American Major League Baseball pitcher who played primarily for the Arizona Diamondbacks in the early 2000s.
-
A.
Jonathan Roberts
Jonathan Roberts is an American screenwriter best known for co-writing Disney’s animated classic "The Lion King."
-
B.
Douglas Guilfoyle
Douglas Guilfoyle is an international law scholar known for his work on the law of the sea, maritime security, and international criminal law.
-
C.
Chris Addison
Chris Addison is a British comedian, actor, writer, and director best known for his work on the political satire series "The Thick of It" and its film spin-off "In the Loop."
-
D.
Paul Givan
Paul Givan is a Democratic Unionist Party politician who served as First Minister of Northern Ireland.
-
E.
Paul Guilfoyle
Paul Guilfoyle is an American actor best known for playing Captain Jim Brass on the long-running television series CSI: Crime Scene Investigation.
- 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc13c9514819096adf60b15016b8b |
completed | March 8, 2026, 6:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b40304a2e08190bcf25ddaf2bc5a2a |
completed | March 13, 2026, 12:28 p.m. |
| NEDg | Description generation | batch_69b406f095488190b4543fa8008fe86c |
completed | March 13, 2026, 12:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b40872099c81909bc3531bea77f875 |
completed | March 13, 2026, 12:52 p.m. |
Created at: March 8, 2026, 3:22 p.m.