Triple
T17796611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniela Amodei |
E444308
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Anthropic |
—
|
NE NERFINISHED |
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: Anthropic | Statement: [Daniela Amodei, employer, Anthropic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anthropic Context triple: [Daniela Amodei, employer, Anthropic]
-
A.
Anthropic
chosen
Anthropic is an American artificial intelligence company known for developing advanced AI systems and research focused on safety and alignment.
-
B.
Ansonian
Ansonian refers to a person from or relating to the city of Ansonia, typically in Connecticut, United States.
-
C.
Lucid
Lucid is the surname of American biochemist and NASA astronaut Shannon Lucid, known for her long-duration spaceflights and record-setting time spent in orbit.
-
D.
Lucid
Lucid is an American luxury electric vehicle brand known for its high-performance, long-range sedans and advanced EV technology.
-
E.
Lucid
"Lucid" is a dance-pop single by Japanese-British singer-songwriter Rina Sawayama, known for its glossy production and euphoric, club-ready sound.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487fafc2c8190b28e791267c47e3c |
completed | April 19, 2026, 7:44 a.m. |
Created at: April 10, 2026, 10:13 a.m.