Triple
T12724879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friant, California |
E304077
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Thomas Friant
Thomas Friant was a U.S. Navy officer after whom the community of Friant, California, was named.
|
E999217
|
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: Thomas Friant | Statement: [Friant, California, namedAfter, Thomas Friant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Friant Context triple: [Friant, California, namedAfter, Thomas Friant]
-
A.
Lee Tourneau
Lee Tourneau is a fictional character from the film "Horns," known for his involvement in the dark, supernatural events surrounding the protagonist.
-
B.
Gene Ramey
Gene Ramey was an American jazz double bassist known for his work in the Kansas City jazz scene and collaborations with leading swing and bebop musicians.
-
C.
Lee Gilmer
Lee Gilmer was an individual significant enough to local aviation or the surrounding community that a regional airport was named in his honor.
-
D.
Grant Wistrom
Grant Wistrom is a former American football defensive end best known for his standout college career at the University of Nebraska and his Super Bowl–winning tenure in the NFL with the St. Louis Rams.
-
E.
Joseph Tinney
Joseph Tinney was the husband of American actress and television producer Judy Lewis.
- 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: Thomas Friant Triple: [Friant, California, namedAfter, Thomas Friant]
Generated description
Thomas Friant was a U.S. Navy officer after whom the community of Friant, California, was named.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Friant Target entity description: Thomas Friant was a U.S. Navy officer after whom the community of Friant, California, was named.
-
A.
Lee Tourneau
Lee Tourneau is a fictional character from the film "Horns," known for his involvement in the dark, supernatural events surrounding the protagonist.
-
B.
Gene Ramey
Gene Ramey was an American jazz double bassist known for his work in the Kansas City jazz scene and collaborations with leading swing and bebop musicians.
-
C.
Lee Gilmer
Lee Gilmer was an individual significant enough to local aviation or the surrounding community that a regional airport was named in his honor.
-
D.
Grant Wistrom
Grant Wistrom is a former American football defensive end best known for his standout college career at the University of Nebraska and his Super Bowl–winning tenure in the NFL with the St. Louis Rams.
-
E.
Joseph Tinney
Joseph Tinney was the husband of American actress and television producer Judy Lewis.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d964148f988190a4d0e7b41614fa64 |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c85c6b88190bbdd94a43915a7a4 |
completed | May 2, 2026, 10:36 p.m. |
| NEDg | Description generation | batch_69f67d888d7c8190b9aaeb877984a403 |
completed | May 2, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67e12b8148190958b63ba114d6221 |
completed | May 2, 2026, 10:43 p.m. |
Created at: April 9, 2026, 5:25 p.m.