Triple
T6059523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Kajaki |
E134998
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object |
Kajaki
Kajaki is a town and district in Afghanistan’s Helmand Province, known for its strategic dam and as a focal point of intense military conflict during the Afghan War.
|
E567075
|
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: Kajaki | Statement: [Battle of Kajaki, location, Kajaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kajaki Context triple: [Battle of Kajaki, location, Kajaki]
-
A.
Kawki
Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
-
B.
Kaiyukan
Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
-
C.
Kaikesi
Kaikesi is a figure in the Hindu epic Ramayana, known as the rakshasi queen of Lanka and the mother of Ravana, Kumbhakarna, and Vibhishana.
-
D.
Syukuro
Syukuro is the given name of Syukuro Manabe, a pioneering climatologist known for his foundational work on climate modeling and global warming.
-
E.
Kapooka
Kapooka is a locality near Wagga Wagga in New South Wales, Australia, best known as the site of a major Australian Army recruit training base.
- 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: Kajaki Triple: [Battle of Kajaki, location, Kajaki]
Generated description
Kajaki is a town and district in Afghanistan’s Helmand Province, known for its strategic dam and as a focal point of intense military conflict during the Afghan War.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kajaki Target entity description: Kajaki is a town and district in Afghanistan’s Helmand Province, known for its strategic dam and as a focal point of intense military conflict during the Afghan War.
-
A.
Kawki
Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
-
B.
Kaiyukan
Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
-
C.
Kaikesi
Kaikesi is a figure in the Hindu epic Ramayana, known as the rakshasi queen of Lanka and the mother of Ravana, Kumbhakarna, and Vibhishana.
-
D.
Syukuro
Syukuro is the given name of Syukuro Manabe, a pioneering climatologist known for his foundational work on climate modeling and global warming.
-
E.
Kapooka
Kapooka is a locality near Wagga Wagga in New South Wales, Australia, best known as the site of a major Australian Army recruit training base.
- 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0571e479c8190bec0e1439b4cf68f |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d13627081908a4b1d758ecb8ddc |
completed | March 23, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_69c11da387dc819088fc37ea1c3daed8 |
completed | March 23, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11e5efd848190adb834e42b4bdc9e |
completed | March 23, 2026, 11:05 a.m. |
Created at: March 22, 2026, 4:10 p.m.