Triple
T15856832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potter County |
E384480
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Robert Potter
Robert Potter was a 19th-century American politician and Texas revolutionary leader whose prominence in early Texas history led to a county being named in his honor.
|
E1179573
|
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: Robert Potter | Statement: [Potter County, namedAfter, Robert Potter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Potter Context triple: [Potter County, namedAfter, Robert Potter]
-
A.
Jack Potter
Jack Potter is the central character of Stephen Crane's short story "The Bride Comes to Yellow Sky," a small-town marshal whose secret marriage disrupts the expectations of his rough Western community.
-
B.
Daniel Potter
Daniel Potter is known as the son of American actress Monica Potter.
-
C.
Mark Potter
Mark Potter is the guitarist for the English alternative rock band Elbow.
-
D.
Richard Pottier
Richard Pottier was a French film director known for his prolific work in popular comedies and dramas from the 1930s to the 1950s.
-
E.
William Ashburner
William Ashburner was a 19th-century American mining engineer and geologist known for his work in mineral surveying and resource assessment in the western United States.
- 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: Robert Potter Triple: [Potter County, namedAfter, Robert Potter]
Generated description
Robert Potter was a 19th-century American politician and Texas revolutionary leader whose prominence in early Texas history led to a county being named in his honor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Robert Potter Target entity description: Robert Potter was a 19th-century American politician and Texas revolutionary leader whose prominence in early Texas history led to a county being named in his honor.
-
A.
Jack Potter
Jack Potter is the central character of Stephen Crane's short story "The Bride Comes to Yellow Sky," a small-town marshal whose secret marriage disrupts the expectations of his rough Western community.
-
B.
Daniel Potter
Daniel Potter is known as the son of American actress Monica Potter.
-
C.
Mark Potter
Mark Potter is the guitarist for the English alternative rock band Elbow.
-
D.
Richard Pottier
Richard Pottier was a French film director known for his prolific work in popular comedies and dramas from the 1930s to the 1950s.
-
E.
William Ashburner
William Ashburner was a 19th-century American mining engineer and geologist known for his work in mineral surveying and resource assessment in the western United States.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e14cb08bd081908af2120eb2925441 |
completed | April 16, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa14c1e508190a182db216cc4e326 |
completed | May 9, 2026, 9:04 p.m. |
| NEDg | Description generation | batch_69ffa41a86ec8190b46d541965ecf26e |
completed | May 9, 2026, 9:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffa496f3e48190b8dc82bece548aec |
completed | May 9, 2026, 9:18 p.m. |
Created at: April 10, 2026, 4:50 a.m.