Triple
T13969480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Page |
E336015
|
entity |
| Predicate | hasDefeated |
P22900
|
FINISHED |
| Object |
Derek Anderson
Derek Anderson is a professional mixed martial artist who has competed in major organizations such as Bellator MMA.
|
E1071070
|
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: Derek Anderson | Statement: [Michael Page, hasDefeated, Derek Anderson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Derek Anderson Context triple: [Michael Page, hasDefeated, Derek Anderson]
-
A.
Derek Anderson
Derek Anderson is a film producer best known for his work on major Hollywood action and science-fiction projects.
-
B.
Derek Rivers
Derek Rivers is an American football defensive end who has played in the NFL, most notably after being drafted by the New England Patriots.
-
C.
Derek Richardson
Derek Richardson is an American actor known for roles in films like "Dumb and Dumberer: When Harry Met Lloyd" and TV series such as "Men in Trees" and "Anger Management."
-
D.
Derek Collison
Derek Collison is a software engineer and entrepreneur best known as the creator of the NATS messaging system and founder of Synadia Communications.
-
E.
Deron Bennett
Deron Bennett is a professional comic book letterer known for his work on various titles across major publishers.
- 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: Derek Anderson Triple: [Michael Page, hasDefeated, Derek Anderson]
Generated description
Derek Anderson is a professional mixed martial artist who has competed in major organizations such as Bellator MMA.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Derek Anderson Target entity description: Derek Anderson is a professional mixed martial artist who has competed in major organizations such as Bellator MMA.
-
A.
Derek Anderson
Derek Anderson is a film producer best known for his work on major Hollywood action and science-fiction projects.
-
B.
Derek Rivers
Derek Rivers is an American football defensive end who has played in the NFL, most notably after being drafted by the New England Patriots.
-
C.
Derek Richardson
Derek Richardson is an American actor known for roles in films like "Dumb and Dumberer: When Harry Met Lloyd" and TV series such as "Men in Trees" and "Anger Management."
-
D.
Derek Collison
Derek Collison is a software engineer and entrepreneur best known as the creator of the NATS messaging system and founder of Synadia Communications.
-
E.
Deron Bennett
Deron Bennett is a professional comic book letterer known for his work on various titles across major publishers.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8daeac8190aadd4b3b60222482 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1dc838c8190bbcfefd69ea29965 |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba2b8e32081909cd32ed0bd255072 |
completed | May 6, 2026, 8:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba322460c81909aa36b661f39efcd |
completed | May 6, 2026, 8:22 p.m. |
Created at: April 9, 2026, 10:18 p.m.