Triple
T12393588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliot Indian Bible |
E296058
|
entity |
| Predicate | printer |
P7012
|
FINISHED |
| Object |
Samuel Green
Samuel Green was a 17th-century colonial American printer best known for producing the Eliot Indian Bible, one of the earliest Bible translations into a Native American language.
|
E982825
|
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: Samuel Green | Statement: [Eliot Indian Bible, printer, Samuel Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samuel Green Context triple: [Eliot Indian Bible, printer, Samuel Green]
-
A.
Samuel Lester
Samuel Lester is the full given name of Les Snead, the American football executive best known as the general manager of the Los Angeles Rams.
-
B.
Samuel Murray
Samuel Murray was an American sculptor known for his public monuments and portrait statues in the late 19th and early 20th centuries.
-
C.
Samuel Benn
Samuel Benn was a 19th-century American settler and entrepreneur credited as the founder of the city of Aberdeen in Washington State.
-
D.
Samuel Barnes
Samuel Barnes is a music producer best known for his work on the album "Faith."
-
E.
Samuel Barnes
Samuel Barnes is an author known for his work with the Juicy brand.
- 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: Samuel Green Triple: [Eliot Indian Bible, printer, Samuel Green]
Generated description
Samuel Green was a 17th-century colonial American printer best known for producing the Eliot Indian Bible, one of the earliest Bible translations into a Native American language.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samuel Green Target entity description: Samuel Green was a 17th-century colonial American printer best known for producing the Eliot Indian Bible, one of the earliest Bible translations into a Native American language.
-
A.
Samuel Lester
Samuel Lester is the full given name of Les Snead, the American football executive best known as the general manager of the Los Angeles Rams.
-
B.
Samuel Murray
Samuel Murray was an American sculptor known for his public monuments and portrait statues in the late 19th and early 20th centuries.
-
C.
Samuel Benn
Samuel Benn was a 19th-century American settler and entrepreneur credited as the founder of the city of Aberdeen in Washington State.
-
D.
Samuel Barnes
Samuel Barnes is a music producer best known for his work on the album "Faith."
-
E.
Samuel Barnes
Samuel Barnes is an author known for his work with the Juicy brand.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd228488190b216abd1c341563c |
completed | April 10, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6347c239881909a031e9e195080c9 |
completed | May 2, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69f63674aa3c81908ba82a9d246b3b3a |
completed | May 2, 2026, 5:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f63a9b32fc8190ab98492ff91d2a66 |
completed | May 2, 2026, 5:55 p.m. |
Created at: April 8, 2026, 9:54 p.m.