Triple
T648413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brownson Deep |
E11291
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Brownson
Brownson is the namesake of the undersea Brownson Deep, likely a notable individual after whom this oceanic feature was designated.
|
E81105
|
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: Brownson | Statement: [Brownson Deep, namedAfter, Brownson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brownson Context triple: [Brownson Deep, namedAfter, Brownson]
-
A.
Stevens
Stevens is a common English-language surname borne by numerous notable individuals across fields such as sports, politics, arts, and academia.
-
B.
William Beecher
William Beecher was a member of the prominent 19th-century Beecher family, known for its influential religious and social reform figures in American history.
-
C.
James Church
James Church is the pseudonym of a former Western intelligence officer known for his critically acclaimed Inspector O series of detective novels set in North Korea.
-
D.
De Witt
De Witt is a Dutch surname most famously associated with Johan de Witt, a prominent 17th-century statesman of the Dutch Republic.
-
E.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
- 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: Brownson Triple: [Brownson Deep, namedAfter, Brownson]
Generated description
Brownson is the namesake of the undersea Brownson Deep, likely a notable individual after whom this oceanic feature was designated.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brownson Target entity description: Brownson is the namesake of the undersea Brownson Deep, likely a notable individual after whom this oceanic feature was designated.
-
A.
Stevens
Stevens is a common English-language surname borne by numerous notable individuals across fields such as sports, politics, arts, and academia.
-
B.
William Beecher
William Beecher was a member of the prominent 19th-century Beecher family, known for its influential religious and social reform figures in American history.
-
C.
James Church
James Church is the pseudonym of a former Western intelligence officer known for his critically acclaimed Inspector O series of detective novels set in North Korea.
-
D.
De Witt
De Witt is a Dutch surname most famously associated with Johan de Witt, a prominent 17th-century statesman of the Dutch Republic.
-
E.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f308f34819094ba28cfc786051e |
completed | March 1, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a580373e3c81909aa9ff50f3b1e781 |
completed | March 2, 2026, 12:19 p.m. |
| NEDg | Description generation | batch_69a5833e10bc819091dba5bb5ec9ea85 |
completed | March 2, 2026, 12:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a583a35678819087d440a05c7b636d |
completed | March 2, 2026, 12:33 p.m. |
Created at: March 1, 2026, 7:36 p.m.