Triple
T12381377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qua Iboe River |
E295751
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object |
Eket
Eket is a town in Akwa Ibom State, southern Nigeria, known as an important center for the country’s oil and gas industry.
|
E977493
|
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: Eket | Statement: [Qua Iboe River, hasNearbySettlement, Eket]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eket Context triple: [Qua Iboe River, hasNearbySettlement, Eket]
-
A.
Eketāhuna
Eketāhuna is a small rural town in New Zealand’s North Island, known for its farming community and location in the Tararua District.
-
B.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
C.
Evron
Evron is a given name most notably borne by American political scientist and intelligence official Evron Maurice Kirkpatrick.
-
D.
Kalkan
Kalkan is a picturesque seaside town on Turkey’s Mediterranean coast, known for its historic architecture, steep cobbled streets, and upscale tourism.
-
E.
Ramatkal
Ramatkal is the Hebrew term for the Chief of the General Staff, the highest-ranking military officer and top commander of the Israel Defense Forces.
- 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: Eket Triple: [Qua Iboe River, hasNearbySettlement, Eket]
Generated description
Eket is a town in Akwa Ibom State, southern Nigeria, known as an important center for the country’s oil and gas industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eket Target entity description: Eket is a town in Akwa Ibom State, southern Nigeria, known as an important center for the country’s oil and gas industry.
-
A.
Eketāhuna
Eketāhuna is a small rural town in New Zealand’s North Island, known for its farming community and location in the Tararua District.
-
B.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
C.
Evron
Evron is a given name most notably borne by American political scientist and intelligence official Evron Maurice Kirkpatrick.
-
D.
Kalkan
Kalkan is a picturesque seaside town on Turkey’s Mediterranean coast, known for its historic architecture, steep cobbled streets, and upscale tourism.
-
E.
Ramatkal
Ramatkal is the Hebrew term for the Chief of the General Staff, the highest-ranking military officer and top commander of the Israel Defense Forces.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbb3a2481908c2fcb5e6488eb3c |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ac5b46c81908d419e09f5629c37 |
completed | May 2, 2026, 4:48 p.m. |
| NEDg | Description generation | batch_69f62c57a26081908d6903906f6e04f0 |
completed | May 2, 2026, 4:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62d07d3148190a45542c8d43a7077 |
completed | May 2, 2026, 4:57 p.m. |
Created at: April 8, 2026, 9:54 p.m.