Triple
T6864581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ezaki Glico Co., Ltd. |
E158365
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object |
Caplico
Caplico is a Japanese confectionery brand known for its cone-shaped, aerated chocolate snacks produced by Ezaki Glico.
|
E623307
|
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: Caplico | Statement: [Ezaki Glico Co., Ltd., hasBrand, Caplico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caplico Context triple: [Ezaki Glico Co., Ltd., hasBrand, Caplico]
-
A.
Atalaya
Atalaya is a small Peruvian river port town in the Amazon rainforest, serving as a regional hub for transport and trade.
-
B.
Macuspana
Macuspana is a significant urban center and municipality in the Mexican state of Tabasco, known for its role in the region’s political and economic life.
-
C.
Caibiran
Caibiran is a coastal municipality on Biliran Island in the Eastern Visayas region of the Philippines, known for its natural springs and rural landscape.
-
D.
Placencia
Placencia is a popular beach village and tourist destination on the Caribbean coast of southern Belize, known for its sandy peninsula, laid-back atmosphere, and access to nearby reefs and cayes.
-
E.
Pacasmayo
Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
- 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: Caplico Triple: [Ezaki Glico Co., Ltd., hasBrand, Caplico]
Generated description
Caplico is a Japanese confectionery brand known for its cone-shaped, aerated chocolate snacks produced by Ezaki Glico.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caplico Target entity description: Caplico is a Japanese confectionery brand known for its cone-shaped, aerated chocolate snacks produced by Ezaki Glico.
-
A.
Atalaya
Atalaya is a small Peruvian river port town in the Amazon rainforest, serving as a regional hub for transport and trade.
-
B.
Macuspana
Macuspana is a significant urban center and municipality in the Mexican state of Tabasco, known for its role in the region’s political and economic life.
-
C.
Caibiran
Caibiran is a coastal municipality on Biliran Island in the Eastern Visayas region of the Philippines, known for its natural springs and rural landscape.
-
D.
Placencia
Placencia is a popular beach village and tourist destination on the Caribbean coast of southern Belize, known for its sandy peninsula, laid-back atmosphere, and access to nearby reefs and cayes.
-
E.
Pacasmayo
Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
- 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_69c68830cdbc8190a8301c7a9d9f651a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d88af6d88190ac9faa32fa1bfa0e |
completed | March 27, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72ff153d48190a4b0d4e403457fe8 |
completed | March 28, 2026, 1:33 a.m. |
| NEDg | Description generation | batch_69c730e882308190a3fbc61245941338 |
completed | March 28, 2026, 1:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7316a9cc081908c088725cb7626e8 |
completed | March 28, 2026, 1:39 a.m. |
Created at: March 27, 2026, 2:21 p.m.