Triple
T4508965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Congo Free State |
E102002
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Boma
Boma is a historic port city on the Congo River in present-day Democratic Republic of the Congo that served as a major colonial administrative and trading center.
|
E448349
|
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: Boma | Statement: [Congo Free State, capital, Boma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boma Context triple: [Congo Free State, capital, Boma]
-
A.
Boma
Boma is a buffet-style African-inspired restaurant at Disney’s Animal Kingdom Lodge known for its diverse flavors and vibrant, marketplace-like atmosphere.
-
B.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
C.
Dutsin-Ma
Dutsin-Ma is a town in northern Nigeria known for hosting the Federal University Dutsin-Ma and serving as an important local commercial and educational center.
-
D.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
E.
Gokwe
Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
- 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: Boma Triple: [Congo Free State, capital, Boma]
Generated description
Boma is a historic port city on the Congo River in present-day Democratic Republic of the Congo that served as a major colonial administrative and trading center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Boma Target entity description: Boma is a historic port city on the Congo River in present-day Democratic Republic of the Congo that served as a major colonial administrative and trading center.
-
A.
Boma
Boma is a buffet-style African-inspired restaurant at Disney’s Animal Kingdom Lodge known for its diverse flavors and vibrant, marketplace-like atmosphere.
-
B.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
C.
Dutsin-Ma
Dutsin-Ma is a town in northern Nigeria known for hosting the Federal University Dutsin-Ma and serving as an important local commercial and educational center.
-
D.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
E.
Gokwe
Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd571138b88190b68bbfc4300aaf9d |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd7f7c1bd08190bc7b7028a512a466 |
completed | March 20, 2026, 5:10 p.m. |
| NEDg | Description generation | batch_69bd84bae7148190ae201ea5257dd43e |
completed | March 20, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bd857181e4819086b7d0b493fbb9a3 |
completed | March 20, 2026, 5:35 p.m. |
Created at: March 20, 2026, 1:01 p.m.