Triple
T350923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Randi Zuckerberg |
E7439
|
entity |
| Predicate | wrote |
P2831
|
FINISHED |
| Object | Dot. |
E44914
|
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: Dot. | Statement: [Randi Zuckerberg, wrote, Dot.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dot. Context triple: [Randi Zuckerberg, wrote, Dot.]
-
A.
Dot.
chosen
Dot. is a children's animated television series created by Randi Zuckerberg that follows a curious young girl using technology and imagination to explore the world around her.
-
B.
DOT
DOT is the commonly used acronym for the United States Department of Transportation, the federal agency responsible for national transportation policy and infrastructure.
-
C.
Dot Complicated
Dot Complicated is a book by Randi Zuckerberg that explores the impact of technology and social media on modern life and offers guidance on achieving a healthier digital balance.
-
D.
The D
"The D" is a popular nickname for Detroit, a major U.S. city known for its automotive industry, musical heritage, and role in American industrial history.
-
E.
DELTA
DELTA is the radio callsign used by pilots and air traffic control to identify and communicate with Delta Air Lines flights.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e0165b6481909345301df3f2144d |
completed | March 1, 2026, 6:43 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.