Triple
T16903395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Cape St. George |
E424495
|
entity |
| Predicate | JapaneseShipParticipated |
P681
|
FINISHED |
| Object |
Makinami
Makinami was a Japanese destroyer of the Imperial Japanese Navy that served in World War II, notably in Pacific naval engagements.
|
E1271370
|
NE FINISHED |
How this triple was built (4 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: Makinami | Statement: [Battle of Cape St. George, JapaneseShipParticipated, Makinami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makinami Context triple: [Battle of Cape St. George, JapaneseShipParticipated, Makinami]
-
A.
Maruim
Maruim is a municipality in the Brazilian state of Sergipe, located along the Sergipe River and known for its historical and regional cultural significance.
-
B.
Shimamoto
Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
-
C.
Fujinami
Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
-
D.
Kizuki
Kizuki is a pivotal, emotionally fragile character in Haruki Murakami's novel "Norwegian Wood," whose death profoundly shapes the lives of those close to him.
-
E.
Ōjin
Ōjin is a semi-legendary early Japanese emperor traditionally regarded as the 15th ruler of Japan and later venerated as the Shinto war deity Hachiman.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Makinami Triple: [Battle of Cape St. George, JapaneseShipParticipated, Makinami]
Generated description
Makinami was a Japanese destroyer of the Imperial Japanese Navy that served in World War II, notably in Pacific naval engagements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Makinami Target entity description: Makinami was a Japanese destroyer of the Imperial Japanese Navy that served in World War II, notably in Pacific naval engagements.
-
A.
Maruim
Maruim is a municipality in the Brazilian state of Sergipe, located along the Sergipe River and known for its historical and regional cultural significance.
-
B.
Shimamoto
Shimamoto is a town in Osaka Prefecture, Japan, located between Kyoto and Osaka along the Yodo River.
-
C.
Fujinami
Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
-
D.
Kizuki
Kizuki is a pivotal, emotionally fragile character in Haruki Murakami's novel "Norwegian Wood," whose death profoundly shapes the lives of those close to him.
-
E.
Ōjin
Ōjin is a semi-legendary early Japanese emperor traditionally regarded as the 15th ruler of Japan and later venerated as the Shinto war deity Hachiman.
- F. None of above. chosen
Provenance (5 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8de3070819085bfe9696bc887ea |
completed | April 18, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01c1e589e081908b12287aa3b05bb6 |
completed | May 11, 2026, 11:47 a.m. |
| NEDg | Description generation | batch_6a01c2c7e32c8190a17307722f5eb50d |
completed | May 11, 2026, 11:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01c33ec9c0819081f7ab7cd8c0eb42 |
completed | May 11, 2026, 11:53 a.m. |
Created at: April 10, 2026, 5:30 a.m.