Triple
T17116910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanacaste Province |
E415361
|
entity |
| Predicate | hasTouristDestination |
P6629
|
FINISHED |
| Object |
Samara
Samara is a laid-back beach town on Costa Rica’s Pacific coast, known for its calm bay, palm-lined shoreline, and appeal to surfers and eco-tourists.
|
E1266249
|
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: Samara | Statement: [Guanacaste Province, hasTouristDestination, Samara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samara Context triple: [Guanacaste Province, hasTouristDestination, Samara]
-
A.
Samara
Samara is a design-focused housing and urban innovation company co-founded by Airbnb’s Joe Gebbia to explore new forms of living and community.
-
B.
Samara
Samara is a city in northwestern Nigeria that forms part of the urban area of Zaria in Kaduna State.
-
C.
Samara
Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
-
D.
Lesosibirsk
Lesosibirsk is a town in central Siberia, Russia, known historically as a major timber-processing and river port center on the Yenisei River.
-
E.
Kazan
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
- 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: Samara Triple: [Guanacaste Province, hasTouristDestination, Samara]
Generated description
Samara is a laid-back beach town on Costa Rica’s Pacific coast, known for its calm bay, palm-lined shoreline, and appeal to surfers and eco-tourists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samara Target entity description: Samara is a laid-back beach town on Costa Rica’s Pacific coast, known for its calm bay, palm-lined shoreline, and appeal to surfers and eco-tourists.
-
A.
Samara
Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
-
B.
Samara
Samara is a design-focused housing and urban innovation company co-founded by Airbnb’s Joe Gebbia to explore new forms of living and community.
-
C.
Samara
Samara is a city in northwestern Nigeria that forms part of the urban area of Zaria in Kaduna State.
-
D.
Lesosibirsk
Lesosibirsk is a town in central Siberia, Russia, known historically as a major timber-processing and river port center on the Yenisei River.
-
E.
Kazan
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e80660048190832d8f91415dd7d7 |
completed | April 18, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a019fdc21148190b20c125773d8a181 |
completed | May 11, 2026, 9:22 a.m. |
| NEDg | Description generation | batch_6a01a15d95d8819097287d678cb8dd59 |
completed | May 11, 2026, 9:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01a1c415dc8190ba8f7e2a8053917f |
completed | May 11, 2026, 9:30 a.m. |
Created at: April 10, 2026, 5:35 a.m.