Triple
T959416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Bigelow |
E20700
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Bigelow
Bigelow is a surname of English origin borne by various notable individuals in fields such as science, politics, and the arts.
|
E113330
|
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: Bigelow | Statement: [Jacob Bigelow, familyName, Bigelow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bigelow Context triple: [Jacob Bigelow, familyName, Bigelow]
-
A.
The Whiting
The Whiting is a prominent performing arts center in Flint, Michigan, hosting concerts, theater productions, and other live cultural events.
-
B.
Seabreeze
Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
-
C.
The Big Tuna
The Big Tuna is the famous nickname of Bill Parcells, a Hall of Fame NFL head coach known for turning struggling teams into contenders.
-
D.
Wellfleet
Wellfleet is a coastal town on outer Cape Cod in Massachusetts known for its oysters, beaches, and protected seashore.
-
E.
Brewster
Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
- 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: Bigelow Triple: [Jacob Bigelow, familyName, Bigelow]
Generated description
Bigelow is a surname of English origin borne by various notable individuals in fields such as science, politics, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bigelow Target entity description: Bigelow is a surname of English origin borne by various notable individuals in fields such as science, politics, and the arts.
-
A.
The Whiting
The Whiting is a prominent performing arts center in Flint, Michigan, hosting concerts, theater productions, and other live cultural events.
-
B.
Seabreeze
Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
-
C.
The Big Tuna
The Big Tuna is the famous nickname of Bill Parcells, a Hall of Fame NFL head coach known for turning struggling teams into contenders.
-
D.
Wellfleet
Wellfleet is a coastal town on outer Cape Cod in Massachusetts known for its oysters, beaches, and protected seashore.
-
E.
Brewster
Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b412f9f48190be123e8c20f38962 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac11a212f08190ae2aad947226d09c |
completed | March 7, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69ac131c23f08190bbdfba76728c8e9f |
completed | March 7, 2026, 11:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac139f1db48190968763d8ae34658d |
completed | March 7, 2026, 12:01 p.m. |
Created at: March 1, 2026, 7:40 p.m.