Triple
T7592961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarō |
E179783
|
entity |
| Predicate | alternativeRomanization |
P5923
|
FINISHED |
| Object | Taro |
E33651
|
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: Taro | Statement: [Tarō, alternativeRomanization, Taro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taro Context triple: [Tarō, alternativeRomanization, Taro]
-
A.
Taro
chosen
Taro is a common Japanese male given name, often written with kanji meaning "eldest son" or similar traditional connotations.
-
B.
Taro
The Taro is a river in northern Italy that flows through the Emilia-Romagna region and ultimately joins the Po River.
-
C.
Takaro
Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
-
D.
Shiso
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
-
E.
Tocho
Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
- 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_69c69f3487ec8190bf7acdf2dd91e6d6 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9b92c348190b547f0aacfb8d6be |
completed | March 27, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c86197fe0881908307a411cabdca7f |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:53 p.m.