Triple
T19401748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam Back |
E485340
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Wei Dai |
—
|
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: Wei Dai | Statement: [Adam Back, collaboratedWith, Wei Dai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wei Dai Context triple: [Adam Back, collaboratedWith, Wei Dai]
-
A.
Wei Dai
chosen
Wei Dai is a computer scientist and cryptographer best known for proposing the b-money concept, an early precursor to modern cryptocurrencies and Bitcoin.
-
B.
Reynold Xin
Reynold Xin is a computer scientist and entrepreneur best known as a co-founder and chief architect of Databricks and a key contributor to Apache Spark.
-
C.
Gong Liu
Gong Liu was an early Zhou dynasty leader credited with consolidating and expanding the Zhou clan, laying foundations for the later rise of the Zhou state in ancient China.
-
D.
William Wang
William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
-
E.
Wang Yitang
Wang Yitang was a Chinese politician and warlord-era figure associated with the Anhui clique during the early Republic of China.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62577454c81909d5bcd07e99b27e4 |
completed | April 20, 2026, 1:09 p.m. |
Created at: April 10, 2026, 1:36 p.m.