Triple
T9723407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur R. von Hippel |
E235539
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arthur |
E270757
|
NE FINISHED |
How this triple was built (2 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: Arthur | Statement: [Arthur R. von Hippel, givenName, Arthur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arthur Context triple: [Arthur R. von Hippel, givenName, Arthur]
-
A.
Arthur
Arthur is a long-running animated children's television series that follows the everyday adventures and life lessons of Arthur Read, an anthropomorphic aardvark, and his friends and family.
-
B.
Arthur
Arthur is a central character, likely a leader or protagonist, around whom allies such as Goosefat Bill rally in a shared cause or conflict.
-
C.
Arthur
Arthur is the given name of Arthur Coningham, a notable British Royal Air Force commander during the World Wars.
-
D.
Arthur
Arthur is a common English-language surname borne by figures such as Chester A. Arthur, the 21st president of the United States.
-
E.
Arthur
chosen
Arthur is the given first name of the influential British computer scientist Robin Milner, known for his work in programming language theory and process calculi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e75abd48190a6e6679ec51496e8 |
completed | April 1, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19fa5a8e48190b7b1742eb6c3b81e |
completed | April 4, 2026, 11:32 p.m. |
Created at: March 30, 2026, 8:20 p.m.