Triple
T13959595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ampara District |
E335756
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Karaitivu
Karaitivu is a coastal town in Sri Lanka’s Eastern Province known for its fishing community and proximity to the Bay of Bengal.
|
E1071435
|
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: Karaitivu | Statement: [Ampara District, hasSettlement, Karaitivu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karaitivu Context triple: [Ampara District, hasSettlement, Karaitivu]
-
A.
Karait
Karait is a small but deadly brown snake in Rudyard Kipling’s “Rikki-Tikki-Tavi,” known as one of the venomous antagonists threatening the human family.
-
B.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
-
C.
Kasari
Kasari is a town located on Amami Ōshima in Japan’s Kagoshima Prefecture, known for its subtropical island scenery and coastal environment.
-
D.
Tekari
Tekari is a town in the Gaya district of Bihar, India, known historically as a local estate center and regional market hub.
-
E.
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.
- 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: Karaitivu Triple: [Ampara District, hasSettlement, Karaitivu]
Generated description
Karaitivu is a coastal town in Sri Lanka’s Eastern Province known for its fishing community and proximity to the Bay of Bengal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karaitivu Target entity description: Karaitivu is a coastal town in Sri Lanka’s Eastern Province known for its fishing community and proximity to the Bay of Bengal.
-
A.
Karait
Karait is a small but deadly brown snake in Rudyard Kipling’s “Rikki-Tikki-Tavi,” known as one of the venomous antagonists threatening the human family.
-
B.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
-
C.
Kasari
Kasari is a town located on Amami Ōshima in Japan’s Kagoshima Prefecture, known for its subtropical island scenery and coastal environment.
-
D.
Tekari
Tekari is a town in the Gaya district of Bihar, India, known historically as a local estate center and regional market hub.
-
E.
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.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7b2f908190aa32f22298964746 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1d490048190b28cb44dd4ec46c4 |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba5646cb48190acd932f6fbd6fe62 |
completed | May 6, 2026, 8:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba6525d0c8190a1ab15881030c11c |
completed | May 6, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:17 p.m.