Triple
T16789691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mullaitivu District |
E408073
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Oddusuddan
Oddusuddan is a town in Sri Lanka’s Northern Province that gained prominence due to its strategic location and role in the country’s civil conflict.
|
E1233342
|
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: Oddusuddan | Statement: [Mullaitivu District, hasSettlement, Oddusuddan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oddusuddan Context triple: [Mullaitivu District, hasSettlement, Oddusuddan]
-
A.
Gutasaga
Gutasaga is a medieval Old Gutnish saga that recounts the legendary origins, history, and laws of the people of Gotland.
-
B.
Pirmasens
Pirmasens is a town in southwestern Germany, in the state of Rhineland-Palatinate, historically known for its shoe manufacturing industry.
-
C.
Hạfhai
Hạfhai is one of the small outlying islets associated with the Polynesian island of Rotuma in the South Pacific.
-
D.
Belegaer
Belegaer is the vast western ocean of Tolkien’s Middle-earth, separating its lands from the distant continent of Aman.
-
E.
Uttoran
Uttoran is a Bengali film best known for featuring acclaimed actress Madhabi Mukherjee in a prominent role.
- 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: Oddusuddan Triple: [Mullaitivu District, hasSettlement, Oddusuddan]
Generated description
Oddusuddan is a town in Sri Lanka’s Northern Province that gained prominence due to its strategic location and role in the country’s civil conflict.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oddusuddan Target entity description: Oddusuddan is a town in Sri Lanka’s Northern Province that gained prominence due to its strategic location and role in the country’s civil conflict.
-
A.
Gutasaga
Gutasaga is a medieval Old Gutnish saga that recounts the legendary origins, history, and laws of the people of Gotland.
-
B.
Pirmasens
Pirmasens is a town in southwestern Germany, in the state of Rhineland-Palatinate, historically known for its shoe manufacturing industry.
-
C.
Hạfhai
Hạfhai is one of the small outlying islets associated with the Polynesian island of Rotuma in the South Pacific.
-
D.
Belegaer
Belegaer is the vast western ocean of Tolkien’s Middle-earth, separating its lands from the distant continent of Aman.
-
E.
Uttoran
Uttoran is a Bengali film best known for featuring acclaimed actress Madhabi Mukherjee in a prominent role.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a50e18819090a30e1f38e520e0 |
completed | April 18, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab09932c8190ba16a349c4938c16 |
completed | May 10, 2026, 3:58 p.m. |
| NEDg | Description generation | batch_6a00acaf3b8c8190820e0abbdd5f8811 |
completed | May 10, 2026, 4:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00ad4bb7a08190ba93bb05435e66b1 |
completed | May 10, 2026, 4:07 p.m. |
Created at: April 10, 2026, 5:22 a.m.