Triple
T19204134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinondoni |
E480186
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Msasani
Msasani is a coastal residential and commercial neighborhood in Dar es Salaam, Tanzania, known for its beaches, nightlife, and expatriate community.
|
E1365247
|
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: Msasani | Statement: [Kinondoni, contains, Msasani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Msasani Context triple: [Kinondoni, contains, Msasani]
-
A.
Mabasa
Mabasa is a barangay (village-level administrative division) within the municipality of Argao in Cebu, Philippines.
-
B.
Moingwena
The Moingwena were a Native American group historically associated with the Illinois (Illiniwek) confederation in the central Mississippi River region.
-
C.
Makoni
Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
-
D.
Mkushi
Mkushi is a farming and trading town in Zambia known for its commercial agriculture, particularly large-scale commercial farming.
-
E.
Mvila
Mvila is an administrative department in Cameroon's South Region, known for its local governance role and regional cultural diversity.
- 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: Msasani Triple: [Kinondoni, contains, Msasani]
Generated description
Msasani is a coastal residential and commercial neighborhood in Dar es Salaam, Tanzania, known for its beaches, nightlife, and expatriate community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Msasani Target entity description: Msasani is a coastal residential and commercial neighborhood in Dar es Salaam, Tanzania, known for its beaches, nightlife, and expatriate community.
-
A.
Mabasa
Mabasa is a barangay (village-level administrative division) within the municipality of Argao in Cebu, Philippines.
-
B.
Moingwena
The Moingwena were a Native American group historically associated with the Illinois (Illiniwek) confederation in the central Mississippi River region.
-
C.
Makoni
Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
-
D.
Mkushi
Mkushi is a farming and trading town in Zambia known for its commercial agriculture, particularly large-scale commercial farming.
-
E.
Mvila
Mvila is an administrative department in Cameroon's South Region, known for its local governance role and regional cultural diversity.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5f99b37c081908c13e0b4cca52aa4 |
completed | April 20, 2026, 10:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0700de73948190a22ce83fa351f099 |
completed | May 15, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_6a07028a76ec8190a73f5ad24d380855 |
completed | May 15, 2026, 11:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0703248b748190b683455342da7238 |
completed | May 15, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:16 p.m.