Triple
T19359932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iringa Region |
E484249
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Kilolo
Kilolo is a town in southern Tanzania that serves as an administrative and local commercial center within the Iringa Region.
|
E1372109
|
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: Kilolo | Statement: [Iringa Region, hasTown, Kilolo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kilolo Context triple: [Iringa Region, hasTown, Kilolo]
-
A.
Libolo
Libolo is a municipality located in Angola’s Cuanza Sul Province, known for its rural communities and agricultural activities.
-
B.
Kilana
Kilana is a Vorta official serving the Dominion who appears in Star Trek: Deep Space Nine as a cunning and diplomatic antagonist.
-
C.
Liholiho
Liholiho, later known as Kamehameha II, was a king of the Kingdom of Hawaii who is remembered for ending the traditional kapu system and helping usher in major cultural and religious changes in the islands.
-
D.
Kilowog
Kilowog is a powerful alien member of the Green Lantern Corps, best known as the gruff but loyal drill instructor who trains new Green Lanterns.
-
E.
Kolu
Kolu is a small village located in Järva County in central Estonia.
- 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: Kilolo Triple: [Iringa Region, hasTown, Kilolo]
Generated description
Kilolo is a town in southern Tanzania that serves as an administrative and local commercial center within the Iringa Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kilolo Target entity description: Kilolo is a town in southern Tanzania that serves as an administrative and local commercial center within the Iringa Region.
-
A.
Libolo
Libolo is a municipality located in Angola’s Cuanza Sul Province, known for its rural communities and agricultural activities.
-
B.
Kilana
Kilana is a Vorta official serving the Dominion who appears in Star Trek: Deep Space Nine as a cunning and diplomatic antagonist.
-
C.
Liholiho
Liholiho, later known as Kamehameha II, was a king of the Kingdom of Hawaii who is remembered for ending the traditional kapu system and helping usher in major cultural and religious changes in the islands.
-
D.
Kilowog
Kilowog is a powerful alien member of the Green Lantern Corps, best known as the gruff but loyal drill instructor who trains new Green Lanterns.
-
E.
Kolu
Kolu is a small village located in Järva County in central Estonia.
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6190b343c81909734ba776fd196dc |
completed | April 20, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07240f812c8190b101fa988defb96f |
completed | May 15, 2026, 1:47 p.m. |
| NEDg | Description generation | batch_6a07250f236c8190b32adebcae3745af |
completed | May 15, 2026, 1:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0726a79b308190a584bc808f4b2faa |
completed | May 15, 2026, 1:59 p.m. |
Created at: April 10, 2026, 1:34 p.m.