Triple
T4275195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ripgrep |
E97033
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object |
Andrew Gallant
Andrew Gallant is a software engineer best known for creating and maintaining ripgrep, a fast command-line search tool.
|
E427867
|
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 Gallant | Statement: [ripgrep, developer, Andrew Gallant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Gallant Context triple: [ripgrep, developer, Andrew Gallant]
-
A.
Bruce Guerin
Bruce Guerin was an American child actor of the silent film era who appeared in several 1920s motion pictures.
-
B.
Glen Schofield
Glen Schofield is a video game developer and executive best known as the co-creator of the Dead Space series and a leader on major AAA action titles.
-
C.
Jeff Gourson
Jeff Gourson is a film editor known for his work on movies such as the comedy "White Chicks."
-
D.
Tim Gardner
Tim Gardner is a neuroscientist and entrepreneur known for co-founding Neuralink, a company developing advanced brain–computer interface technology.
-
E.
Robert Fortier
Robert Fortier was an American actor known for his character roles in film and television during the mid-20th century.
- 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 Gallant Triple: [ripgrep, developer, Andrew Gallant]
Generated description
Andrew Gallant is a software engineer best known for creating and maintaining ripgrep, a fast command-line search tool.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrew Gallant Target entity description: Andrew Gallant is a software engineer best known for creating and maintaining ripgrep, a fast command-line search tool.
-
A.
Bruce Guerin
Bruce Guerin was an American child actor of the silent film era who appeared in several 1920s motion pictures.
-
B.
Glen Schofield
Glen Schofield is a video game developer and executive best known as the co-creator of the Dead Space series and a leader on major AAA action titles.
-
C.
Jeff Gourson
Jeff Gourson is a film editor known for his work on movies such as the comedy "White Chicks."
-
D.
Tim Gardner
Tim Gardner is a neuroscientist and entrepreneur known for co-founding Neuralink, a company developing advanced brain–computer interface technology.
-
E.
Robert Fortier
Robert Fortier was an American actor known for his character roles in film and television during the mid-20th century.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501c35688190a7d15d904f15f968 |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7b0b2ec819090ccf042917ae207 |
completed | March 14, 2026, 7:32 p.m. |
| NEDg | Description generation | batch_69b5b8ac37c88190ad2c6a8358e17554 |
completed | March 14, 2026, 7:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5b92eec8c81908c114238af39450f |
completed | March 14, 2026, 7:38 p.m. |
Created at: March 12, 2026, 11:07 p.m.