Triple
T23421757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsuyoshi Ihara |
E560673
|
entity |
| Predicate | actedIn |
P1668
|
FINISHED |
| Object |
The K2
The K2 is a South Korean television drama series that follows a former mercenary hired as a bodyguard amid political intrigue and personal revenge.
|
E1586851
|
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: The K2 | Statement: [Tsuyoshi Ihara, actedIn, The K2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The K2 Context triple: [Tsuyoshi Ihara, actedIn, The K2]
-
A.
K2
K2 is the world’s second-highest mountain, a notoriously difficult and dangerous peak in the Karakoram range of the Himalayas.
-
B.
K2
K2 is a prominent outdoor recreation brand best known for its skis, snowboards, and other winter sports equipment.
-
C.
Nanga Parbat
Nanga Parbat is one of the world’s highest and most notoriously challenging mountains, located in the western Himalayas of Pakistan.
-
D.
Stok Kangri
Stok Kangri is a prominent trekking and mountaineering peak in the Indian Himalayas, known for its challenging high-altitude climb and panoramic views over Ladakh.
-
E.
Hathi Parbat
Hathi Parbat is a prominent mountain peak in the Indian Himalayas known for its steep faces and challenging climbing routes near the Valley of Flowers region in Uttarakhand.
- 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: The K2 Triple: [Tsuyoshi Ihara, actedIn, The K2]
Generated description
The K2 is a South Korean television drama series that follows a former mercenary hired as a bodyguard amid political intrigue and personal revenge.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The K2 Target entity description: The K2 is a South Korean television drama series that follows a former mercenary hired as a bodyguard amid political intrigue and personal revenge.
-
A.
K2
K2 is a prominent outdoor recreation brand best known for its skis, snowboards, and other winter sports equipment.
-
B.
K2
K2 is the world’s second-highest mountain, a notoriously difficult and dangerous peak in the Karakoram range of the Himalayas.
-
C.
Nanga Parbat
Nanga Parbat is one of the world’s highest and most notoriously challenging mountains, located in the western Himalayas of Pakistan.
-
D.
Stok Kangri
Stok Kangri is a prominent trekking and mountaineering peak in the Indian Himalayas, known for its challenging high-altitude climb and panoramic views over Ladakh.
-
E.
Hathi Parbat
Hathi Parbat is a prominent mountain peak in the Indian Himalayas known for its steep faces and challenging climbing routes near the Valley of Flowers region in Uttarakhand.
- 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a546c08c8190b57d90e88034eef3 |
completed | April 29, 2026, 6:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c67a372f88190a9cee3c37e4e6507 |
completed | May 19, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_6a0c72156130819082e1d07262e144ca |
completed | May 19, 2026, 2:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c770010308190a0a07b50fdca7d6a |
completed | May 19, 2026, 2:43 p.m. |
Created at: April 17, 2026, 5:46 p.m.