Triple
T20386997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicholas Angel |
E497984
|
entity |
| Predicate | settingOfMainStory |
P1957
|
FINISHED |
| Object |
Sanford
Sanford is the fictional rural English village that serves as the primary setting of the action-comedy film "Hot Fuzz."
|
E1428103
|
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: Sanford | Statement: [Nicholas Angel, settingOfMainStory, Sanford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanford Context triple: [Nicholas Angel, settingOfMainStory, Sanford]
-
A.
Sanford
Sanford is a major American manufacturer of writing instruments, best known as the parent company behind brands like Sharpie and Paper Mate.
-
B.
Sanford
Sanford is a small rural town located in Conejos County in southern Colorado, known for its agricultural surroundings and close-knit community.
-
C.
Sanford
Sanford is a city in central North Carolina that serves as a regional hub for education, industry, and commerce.
-
D.
Sanford
Sanford is a classic American television sitcom best known for its sharp-tongued humor and portrayal of a cantankerous junk dealer and his family in Los Angeles.
-
E.
Sanford
Sanford is an American television sitcom that served as a continuation of the classic series "Sanford and Son," featuring Redd Foxx reprising his role as Fred Sanford.
- 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: Sanford Triple: [Nicholas Angel, settingOfMainStory, Sanford]
Generated description
Sanford is the fictional rural English village that serves as the primary setting of the action-comedy film "Hot Fuzz."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sanford Target entity description: Sanford is the fictional rural English village that serves as the primary setting of the action-comedy film "Hot Fuzz."
-
A.
Sanford
Sanford is a classic American television sitcom best known for its sharp-tongued humor and portrayal of a cantankerous junk dealer and his family in Los Angeles.
-
B.
Sanford
Sanford is a small rural town located in Conejos County in southern Colorado, known for its agricultural surroundings and close-knit community.
-
C.
Sanford
Sanford is a small town located in Covington County in the southern part of the U.S. state of Alabama.
-
D.
Sanford
Sanford is a city in central North Carolina that serves as a regional hub for education, industry, and commerce.
-
E.
Sanford
Sanford is a city in central Florida known as a historic gateway to the region, featuring a busy regional airport and a revitalized downtown on the shores of Lake Monroe.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790c935881908f901d058e6a83a9 |
completed | April 20, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08761d20a48190ad378eba3d22684a |
completed | May 16, 2026, 1:50 p.m. |
| NEDg | Description generation | batch_6a0876f82dac8190a6c25fc0574a842a |
completed | May 16, 2026, 1:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0877ac99408190a31ee21894770334 |
completed | May 16, 2026, 1:57 p.m. |
Created at: April 16, 2026, 11:28 a.m.