Triple
T10780681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thivim railway station |
E254310
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object |
Baga
Baga is a popular coastal town in North Goa, India, best known for its lively beach, nightlife, and tourism.
|
E886373
|
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: Baga | Statement: [Thivim railway station, serves, Baga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baga Context triple: [Thivim railway station, serves, Baga]
-
A.
Baga
The Baga are an ethnic group of coastal Guinea in West Africa, known for their rich artistic traditions, especially wooden masks and sculptures used in ritual ceremonies.
-
B.
Bagà
Bagà is a historic town in Catalonia, Spain, known for its medieval old quarter and location in the Pyrenees.
-
C.
Baguia
Baguia is a remote mountainous region and administrative post in eastern Timor-Leste known for its traditional villages and rugged landscapes.
-
D.
Sidama
Sidama is an ethnic group primarily inhabiting the Sidama Region of southern Ethiopia, known for its distinct Cushitic language and coffee-growing culture.
-
E.
Garoua
Garoua is a major city in northern Cameroon that serves as an important commercial and administrative center and a key hub for river and overland transport in the region.
- 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: Baga Triple: [Thivim railway station, serves, Baga]
Generated description
Baga is a popular coastal town in North Goa, India, best known for its lively beach, nightlife, and tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baga Target entity description: Baga is a popular coastal town in North Goa, India, best known for its lively beach, nightlife, and tourism.
-
A.
Baga
The Baga are an ethnic group of coastal Guinea in West Africa, known for their rich artistic traditions, especially wooden masks and sculptures used in ritual ceremonies.
-
B.
Bagà
Bagà is a historic town in Catalonia, Spain, known for its medieval old quarter and location in the Pyrenees.
-
C.
Baguia
Baguia is a remote mountainous region and administrative post in eastern Timor-Leste known for its traditional villages and rugged landscapes.
-
D.
Sidama
Sidama is an ethnic group primarily inhabiting the Sidama Region of southern Ethiopia, known for its distinct Cushitic language and coffee-growing culture.
-
E.
Garoua
Garoua is a major city in northern Cameroon that serves as an important commercial and administrative center and a key hub for river and overland transport in the region.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c48c488190a2b3162202b74726 |
completed | April 9, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de55fbfc70819098eb40cf0d1b9e8c |
completed | April 14, 2026, 2:58 p.m. |
| NEDg | Description generation | batch_69de5eacae148190b7ca2da87427572e |
completed | April 14, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de6397ff688190b6788489895a5360 |
completed | April 14, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:17 p.m.