Triple
T4389084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dario Amodei |
E99318
|
entity |
| Predicate | previousEmployer |
P1910
|
FINISHED |
| Object | Baidu |
E239156
|
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: Baidu | Statement: [Dario Amodei, previousEmployer, Baidu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baidu Context triple: [Dario Amodei, previousEmployer, Baidu]
-
A.
Baidu
chosen
Baidu is a leading Chinese technology company best known for its dominant search engine and extensive work in artificial intelligence.
-
B.
Goole
Goole is an inland port town in the East Riding of Yorkshire, England, known for its significant docks and role in regional maritime trade.
-
C.
Yandex
Yandex is a major Russian multinational technology company best known for its internet search engine and wide range of online services.
-
D.
Google
Google is a multinational technology company best known for its search engine and wide range of internet-related products and services, including Android, YouTube, and cloud computing.
-
E.
Bing
Bing is Microsoft's web search engine that provides internet search, image, video, and mapping services.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35281900c8190882e9ccfa44ab86f |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e52d63c08190bc98c090cfe0ff1c |
completed | March 14, 2026, 10:46 p.m. |
Created at: March 12, 2026, 11:19 p.m.