Triple
T362016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koop |
E7875
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Tony Koop
Tony Koop is an individual notable enough to be recognized as a namesake of the surname Koop, though specific widely known public details about him are limited.
|
E52375
|
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: Tony Koop | Statement: [Koop, hasNotableBearer, Tony Koop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Koop Context triple: [Koop, hasNotableBearer, Tony Koop]
-
A.
Steven Koop
Steven Koop is an individual notable enough to be specifically identified as a bearer of the surname Koop, though no widely recognized public information about him is available.
-
B.
Bill Koop
Bill Koop is an individual notable enough to be recognized as a prominent bearer of the surname Koop.
-
C.
Jon Bosak
Jon Bosak is a computer scientist best known for leading the original XML specification effort at the World Wide Web Consortium (W3C), which helped standardize data interchange on the web.
-
D.
Doug Koop
Doug Koop is a notable individual recognized for achievements significant enough to be associated with the surname Koop.
-
E.
Daniel Kottke
Daniel Kottke is an early Apple employee and close college friend of Steve Jobs who worked on the original Apple computers.
- 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: Tony Koop Triple: [Koop, hasNotableBearer, Tony Koop]
Generated description
Tony Koop is an individual notable enough to be recognized as a namesake of the surname Koop, though specific widely known public details about him are limited.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tony Koop Target entity description: Tony Koop is an individual notable enough to be recognized as a namesake of the surname Koop, though specific widely known public details about him are limited.
-
A.
Steven Koop
Steven Koop is an individual notable enough to be specifically identified as a bearer of the surname Koop, though no widely recognized public information about him is available.
-
B.
Bill Koop
Bill Koop is an individual notable enough to be recognized as a prominent bearer of the surname Koop.
-
C.
Jon Bosak
Jon Bosak is a computer scientist best known for leading the original XML specification effort at the World Wide Web Consortium (W3C), which helped standardize data interchange on the web.
-
D.
Doug Koop
Doug Koop is a notable individual recognized for achievements significant enough to be associated with the surname Koop.
-
E.
Daniel Kottke
Daniel Kottke is an early Apple employee and close college friend of Steve Jobs who worked on the original Apple computers.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebce64c88190a0a8edcc7095f78b |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a41b44959c8190a793b4e5af838c7c |
completed | March 1, 2026, 10:56 a.m. |
| NEDg | Description generation | batch_69a41bd12bdc81909fc3da7e3a01642b |
completed | March 1, 2026, 10:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a42290059481908d0b10769263b0da |
completed | March 1, 2026, 11:27 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.