Triple
T14018219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emerson |
E337254
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Ken Emerson
Ken Emerson is an American music journalist and cultural historian known for his writings on popular music and its social context.
|
E1081818
|
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: Ken Emerson | Statement: [Emerson, hasNotableBearer, Ken Emerson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Emerson Context triple: [Emerson, hasNotableBearer, Ken Emerson]
-
A.
Nick Emerson
Nick Emerson is a film editor known for his work on the biographical romantic drama "Film Stars Don’t Die in Liverpool."
-
B.
Nick Emerson
Nick Emerson is an editor known for his work on editions of Shakespearean plays, including "Lady Macbeth."
-
C.
Sam Emerson
Sam Emerson is a teenage protagonist in the 1987 horror-comedy film "The Lost Boys," known for battling a gang of vampires alongside his older brother in the coastal town of Santa Carla.
-
D.
Rob Emerson
Rob Emerson is an American mixed martial artist best known for competing in the UFC’s lightweight division and appearing on The Ultimate Fighter reality series.
-
E.
Darren Emerson
Darren Emerson is an English DJ and electronic music producer best known for his influential work in the 1990s progressive house and techno scenes.
- 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: Ken Emerson Triple: [Emerson, hasNotableBearer, Ken Emerson]
Generated description
Ken Emerson is an American music journalist and cultural historian known for his writings on popular music and its social context.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ken Emerson Target entity description: Ken Emerson is an American music journalist and cultural historian known for his writings on popular music and its social context.
-
A.
Nick Emerson
Nick Emerson is a film editor known for his work on the biographical romantic drama "Film Stars Don’t Die in Liverpool."
-
B.
Nick Emerson
Nick Emerson is an editor known for his work on editions of Shakespearean plays, including "Lady Macbeth."
-
C.
Sam Emerson
Sam Emerson is a teenage protagonist in the 1987 horror-comedy film "The Lost Boys," known for battling a gang of vampires alongside his older brother in the coastal town of Santa Carla.
-
D.
Rob Emerson
Rob Emerson is an American mixed martial artist best known for competing in the UFC’s lightweight division and appearing on The Ultimate Fighter reality series.
-
E.
Darren Emerson
Darren Emerson is an English DJ and electronic music producer best known for his influential work in the 1990s progressive house and techno scenes.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f3b5b088190a58715779d2c46a6 |
completed | April 14, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdef5e0648190ace4ec1605968e30 |
completed | May 7, 2026, 6:50 p.m. |
| NEDg | Description generation | batch_69fcdfd372e0819089f0b48f84a63ab4 |
completed | May 7, 2026, 6:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce027c628819085738433b5d5525d |
completed | May 7, 2026, 6:55 p.m. |
Created at: April 9, 2026, 10:19 p.m.