Triple
T16303732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eisai |
E395854
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Eisai |
E24939
|
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: Eisai | Statement: [Eisai, name, Eisai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eisai Context triple: [Eisai, name, Eisai]
-
A.
Eisai
chosen
Eisai is a Japanese pharmaceutical company known for developing treatments in neurology and oncology, including Alzheimer’s disease therapies.
-
B.
Eisai
Eisai was a Japanese Buddhist monk of the Kamakura period best known for introducing Rinzai Zen and promoting tea culture in Japan.
-
C.
Daiichi Sankyo
Daiichi Sankyo is a major Japanese global pharmaceutical company known for developing innovative medicines, particularly in cardiovascular disease and oncology.
-
D.
Chugai Pharmaceutical
Chugai Pharmaceutical is a major Japanese research-based pharmaceutical company known for its innovative biopharmaceuticals and strategic alliance with Roche.
-
E.
Takeda Pharmaceutical Company
Takeda Pharmaceutical Company is a leading global biopharmaceutical firm headquartered in Japan, focused on developing innovative medicines in areas such as oncology, gastroenterology, neuroscience, and rare diseases.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e35157481909e5604b7dae7a2a2 |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001fa16e3c81908a92225b5b57d711 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.