Triple
T17339511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedict Crowell |
E421027
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Benedict Crowell |
E421027
|
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: Benedict Crowell | Statement: [Benedict Crowell, name, Benedict Crowell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benedict Crowell Context triple: [Benedict Crowell, name, Benedict Crowell]
-
A.
Benedict Crowell
chosen
Benedict Crowell was an American engineer, industrialist, and government official who played a key role in organizing U.S. military production during World War I.
-
B.
Andrew Crowell
Andrew Crowell is an individual notable enough to be specifically referenced as a bearer of the Crowell surname.
-
C.
Sam McCandlish
Sam McCandlish is a machine learning researcher known for his work on large-scale language models and contributions to influential AI research at OpenAI.
-
D.
Jonathan Trager
Jonathan Trager is the romantic, fate-obsessed protagonist of the film "Serendipity," whose chance encounter with a woman leads him on a years-long quest to find her again.
-
E.
Andrew Dillin
Andrew Dillin is an American molecular biologist known for his influential research on the genetics of aging and protein homeostasis, particularly using C. elegans as a model organism.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c56c8148190ab6e3e2eff09725e |
completed | May 11, 2026, 7:59 a.m. |
Created at: April 10, 2026, 5:44 a.m.