Triple
T20834593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chimwiini |
E512925
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object |
Brava
Brava is a coastal city in southern Somalia known for its historic Swahili-Arabic cultural heritage and role as a regional trading center on the Indian Ocean.
|
E1453618
|
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: Brava | Statement: [Chimwiini, spokenIn, Brava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brava Context triple: [Chimwiini, spokenIn, Brava]
-
A.
Brava
Brava is a small, mountainous island in the Cape Verde archipelago known for its lush vegetation, volcanic landscapes, and traditional Creole culture.
-
B.
Braven
Braven is an action thriller film starring Stephen Lang and Jason Momoa, centered on a logging family’s violent confrontation with drug traffickers at a remote mountain cabin.
-
C.
Wonderbra
Wonderbra is a famous push-up bra brand known for its cleavage-enhancing lingerie and iconic advertising campaigns.
-
D.
Bravo
Bravo is an American cable television network best known for its reality TV programming and pop culture–focused entertainment.
-
E.
Bravo
Bravo is a company best known for operating the Bravo app, a platform that facilitates cashless tipping and payments.
- 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: Brava Triple: [Chimwiini, spokenIn, Brava]
Generated description
Brava is a coastal city in southern Somalia known for its historic Swahili-Arabic cultural heritage and role as a regional trading center on the Indian Ocean.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brava Target entity description: Brava is a coastal city in southern Somalia known for its historic Swahili-Arabic cultural heritage and role as a regional trading center on the Indian Ocean.
-
A.
Brava
Brava is a small, mountainous island in the Cape Verde archipelago known for its lush vegetation, volcanic landscapes, and traditional Creole culture.
-
B.
Braven
Braven is an action thriller film starring Stephen Lang and Jason Momoa, centered on a logging family’s violent confrontation with drug traffickers at a remote mountain cabin.
-
C.
Wonderbra
Wonderbra is a famous push-up bra brand known for its cleavage-enhancing lingerie and iconic advertising campaigns.
-
D.
Bravo
Bravo is an American cable television network best known for its reality TV programming and pop culture–focused entertainment.
-
E.
Bravo
Bravo is a company best known for operating the Bravo app, a platform that facilitates cashless tipping and payments.
- 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_69e0b4cf62a88190bbf92351e9e57259 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c32622c481908b8d2159bd5bb0ad |
completed | April 21, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a090afd181c81909dba7617c286af58 |
completed | May 17, 2026, 12:25 a.m. |
| NEDg | Description generation | batch_6a090c524a308190bb063e0f5200cef7 |
completed | May 17, 2026, 12:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a090cd6f0048190861b7a93560355aa |
completed | May 17, 2026, 12:33 a.m. |
Created at: April 16, 2026, 12:42 p.m.