Triple
T13425206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthropic |
E313461
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Jared Mueller
Jared Mueller is an entrepreneur best known as a co-founder of the AI safety and research company Anthropic.
|
E1038740
|
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: Jared Mueller | Statement: [Anthropic, foundedBy, Jared Mueller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jared Mueller Context triple: [Anthropic, foundedBy, Jared Mueller]
-
A.
Jared Faber
Jared Faber is an American composer and producer best known for creating music for animated television series and children's programming.
-
B.
Jared Bridgeman
Jared Bridgeman is an American hip hop artist better known by his stage name Akrobatik, recognized for his work in the Boston underground rap scene.
-
C.
Jared Rushton
Jared Rushton is an American former child actor best known for his roles in 1980s films such as "Big" and "Honey, I Shrunk the Kids."
-
D.
Michael Hudecek
Michael Hudecek is a film editor known for his work on the movie "Hidden (Caché)."
-
E.
Matthew Strickland
Matthew Strickland is a historian and academic known for his work on medieval warfare, chivalry, and the nobility in medieval England.
- 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: Jared Mueller Triple: [Anthropic, foundedBy, Jared Mueller]
Generated description
Jared Mueller is an entrepreneur best known as a co-founder of the AI safety and research company Anthropic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jared Mueller Target entity description: Jared Mueller is an entrepreneur best known as a co-founder of the AI safety and research company Anthropic.
-
A.
Jared Faber
Jared Faber is an American composer and producer best known for creating music for animated television series and children's programming.
-
B.
Jared Bridgeman
Jared Bridgeman is an American hip hop artist better known by his stage name Akrobatik, recognized for his work in the Boston underground rap scene.
-
C.
Jared Rushton
Jared Rushton is an American former child actor best known for his roles in 1980s films such as "Big" and "Honey, I Shrunk the Kids."
-
D.
Michael Hudecek
Michael Hudecek is a film editor known for his work on the movie "Hidden (Caché)."
-
E.
Matthew Strickland
Matthew Strickland is a historian and academic known for his work on medieval warfare, chivalry, and the nobility in medieval England.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed066408190a416880affd8416e |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7308673488190a64f4b205899605b |
completed | May 3, 2026, 11:24 a.m. |
| NEDg | Description generation | batch_69f7316101e48190b3ec59a4376a0562 |
completed | May 3, 2026, 11:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f731f8e98c8190becfad8e3a371484 |
completed | May 3, 2026, 11:31 a.m. |
Created at: April 9, 2026, 9:40 p.m.