Triple
T9005626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rob Carpenter |
E215135
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Bobby Carpenter
Bobby Carpenter is a former American professional ice hockey forward who played in the NHL and was one of the first U.S.-born players to score 50 goals in a season.
|
E773406
|
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: Bobby Carpenter | Statement: [Rob Carpenter, child, Bobby Carpenter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobby Carpenter Context triple: [Rob Carpenter, child, Bobby Carpenter]
-
A.
Bobby Dyer
Bobby Dyer is an American politician who serves as the mayor of Virginia Beach, Virginia.
-
B.
Bobby Morrow
Bobby Morrow was an American sprinter and three-time Olympic gold medalist renowned for dominating the 100m and 200m events in the mid-1950s.
-
C.
Bobby Walden
Bobby Walden was an American professional football punter best known for his successful NFL career, particularly with the Pittsburgh Steelers during their 1970s championship era.
-
D.
Bobby Massey
Bobby Massey is an author best known for writing the comic book series "Bound 2."
-
E.
Bobby Bowman
Bobby Bowman is a television writer and producer best known for his work on the comedy series "My Name Is Earl."
- 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: Bobby Carpenter Triple: [Rob Carpenter, child, Bobby Carpenter]
Generated description
Bobby Carpenter is a former American professional ice hockey forward who played in the NHL and was one of the first U.S.-born players to score 50 goals in a season.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bobby Carpenter Target entity description: Bobby Carpenter is a former American professional ice hockey forward who played in the NHL and was one of the first U.S.-born players to score 50 goals in a season.
-
A.
Bobby Dyer
Bobby Dyer is an American politician who serves as the mayor of Virginia Beach, Virginia.
-
B.
Bobby Morrow
Bobby Morrow was an American sprinter and three-time Olympic gold medalist renowned for dominating the 100m and 200m events in the mid-1950s.
-
C.
Bobby Walden
Bobby Walden was an American professional football punter best known for his successful NFL career, particularly with the Pittsburgh Steelers during their 1970s championship era.
-
D.
Bobby Massey
Bobby Massey is an author best known for writing the comic book series "Bound 2."
-
E.
Bobby Bowman
Bobby Bowman is a television writer and producer best known for his work on the comedy series "My Name Is Earl."
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc695afa34819086cf6fcce2997b5f |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb9a11948190a43f60d0df71b1af |
completed | April 3, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69cfdd80d5ac8190862704a62ac1c942 |
completed | April 3, 2026, 3:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfde1eb8588190859a015f61d8f433 |
completed | April 3, 2026, 3:34 p.m. |
Created at: March 30, 2026, 7:05 p.m.