Triple
T17268489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamajaya |
E419191
|
entity |
| Predicate | equatedWith |
P6530
|
FINISHED |
| Object |
Kama
Kama is the Hindu god of love, desire, and attraction, often depicted as a youthful archer who inspires romantic and sensual longing.
|
E1260447
|
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: Kama | Statement: [Kamajaya, equatedWith, Kama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kama Context triple: [Kamajaya, equatedWith, Kama]
-
A.
Kama
Kama is a small city located in Japan’s Fukuoka Prefecture on the island of Kyushu.
-
B.
Kama
Kama is a surname of likely West African origin, notably borne by figures such as Senegalese jurist and former International Criminal Tribunal judge Laïty Kama.
-
C.
Kamari
Kamari is a popular seaside village on the southeast coast of Santorini, Greece, known for its black-sand beach and tourist-friendly promenade.
-
D.
Kaa
Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
-
E.
Tantamani
Tantamani was a Kushite king of the 25th Dynasty of Egypt, known for his brief attempt to restore Nubian control over Egypt before being driven back by the Assyrians.
- 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: Kama Triple: [Kamajaya, equatedWith, Kama]
Generated description
Kama is the Hindu god of love, desire, and attraction, often depicted as a youthful archer who inspires romantic and sensual longing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kama Target entity description: Kama is the Hindu god of love, desire, and attraction, often depicted as a youthful archer who inspires romantic and sensual longing.
-
A.
Kama
Kama is a small city located in Japan’s Fukuoka Prefecture on the island of Kyushu.
-
B.
Kama
Kama is a surname of likely West African origin, notably borne by figures such as Senegalese jurist and former International Criminal Tribunal judge Laïty Kama.
-
C.
Kamari
Kamari is a popular seaside village on the southeast coast of Santorini, Greece, known for its black-sand beach and tourist-friendly promenade.
-
D.
Kaa
Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
-
E.
Tantamani
Tantamani was a Kushite king of the 25th Dynasty of Egypt, known for his brief attempt to restore Nubian control over Egypt before being driven back by the Assyrians.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4683c4819083a210255662136c |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0179482a348190a00dd3cd5076431e |
completed | May 11, 2026, 6:38 a.m. |
| NEDg | Description generation | batch_6a017b6a0ee48190860c4f981003d32e |
completed | May 11, 2026, 6:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a017c3925d081908819faa6b1790bd5 |
completed | May 11, 2026, 6:50 a.m. |
Created at: April 10, 2026, 5:40 a.m.