Triple
T8498604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linus Caldwell |
E201158
|
entity |
| Predicate | worksWith |
P398
|
FINISHED |
| Object | Yen |
E385766
|
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: Yen | Statement: [Linus Caldwell, worksWith, Yen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yen Context triple: [Linus Caldwell, worksWith, Yen]
-
A.
Yen
chosen
Yen is a nimble and acrobatic member of Danny Ocean’s heist crew in the Ocean’s film series, renowned for his contortionist skills.
-
B.
Japanese yen
The Japanese yen is Japan's official fiat currency and one of the world's most traded reserve currencies in global foreign exchange markets.
-
C.
Yuan
Yuan is a common Chinese surname with historical roots and notable bearers in business, politics, and the arts.
-
D.
Chinese yuan
The Chinese yuan is the official currency of the People's Republic of China and one of the world's major reserve and trading currencies.
-
E.
Indonesian rupiah
The Indonesian rupiah is the official currency of Indonesia, known for experiencing severe devaluation during the late-1990s Asian financial crisis.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe583aebc819090345684bfa1fca2 |
completed | March 31, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e0aa7788190abd7bb259966bc44 |
completed | April 2, 2026, 11:07 a.m. |
Created at: March 30, 2026, 6:14 p.m.