Triple
T2601740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Shōken |
E58358
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Haruko |
E156880
|
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: Haruko | Statement: [Empress Shōken, birthName, Haruko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haruko Context triple: [Empress Shōken, birthName, Haruko]
-
A.
Haruko
chosen
Haruko, better known as Empress Shōken, was the consort of Emperor Meiji and a prominent Japanese empress noted for her support of modernization and social welfare.
-
B.
Atsuko
Atsuko is a Japanese feminine given name commonly borne by women and princesses in Japan, with meanings that vary depending on the kanji used.
-
C.
Yuriko
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
-
D.
Kazuko
Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
-
E.
Totsuko
Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd459ca6c81908505be96d097b739 |
completed | March 7, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83d37de081909467f8caa17ce3a9 |
completed | March 10, 2026, 2:37 a.m. |
Created at: March 6, 2026, 9:49 p.m.