Triple
T18246053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurzeme |
E436956
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Roja
Roja is a small coastal town in western Latvia known for its fishing heritage and location on the shores of the Gulf of Riga.
|
E1313438
|
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: Roja | Statement: [Kurzeme, containsTown, Roja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roja Context triple: [Kurzeme, containsTown, Roja]
-
A.
Roja
Roja is a critically acclaimed 1992 Indian Tamil-language political thriller film directed by Mani Ratnam, noted for its powerful storytelling and A. R. Rahman's debut film score.
-
B.
Meenas
The Meenas are an indigenous tribal community of northern India, historically associated with agrarian livelihoods, local chieftaincies, and a distinct cultural and religious heritage.
-
C.
Zinda Rood
Zinda Rood is a biographical work by Javid Iqbal that chronicles the life, thought, and legacy of his father, the philosopher-poet Muhammad Iqbal.
-
D.
Yannai
Yannai is another name for Alexander Jannaeus, a Hasmonean king of Judea and high priest who ruled in the early 1st century BCE.
-
E.
Mardaani
Mardaani is a 2014 Indian crime thriller film that follows a tough female police officer’s pursuit of a child trafficking racket.
- 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: Roja Triple: [Kurzeme, containsTown, Roja]
Generated description
Roja is a small coastal town in western Latvia known for its fishing heritage and location on the shores of the Gulf of Riga.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roja Target entity description: Roja is a small coastal town in western Latvia known for its fishing heritage and location on the shores of the Gulf of Riga.
-
A.
Roja
Roja is a critically acclaimed 1992 Indian Tamil-language political thriller film directed by Mani Ratnam, noted for its powerful storytelling and A. R. Rahman's debut film score.
-
B.
Meenas
The Meenas are an indigenous tribal community of northern India, historically associated with agrarian livelihoods, local chieftaincies, and a distinct cultural and religious heritage.
-
C.
Zinda Rood
Zinda Rood is a biographical work by Javid Iqbal that chronicles the life, thought, and legacy of his father, the philosopher-poet Muhammad Iqbal.
-
D.
Yannai
Yannai is another name for Alexander Jannaeus, a Hasmonean king of Judea and high priest who ruled in the early 1st century BCE.
-
E.
Mardaani
Mardaani is a 2014 Indian crime thriller film that follows a tough female police officer’s pursuit of a child trafficking racket.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e6fbac8190bf252c4337f50c29 |
completed | April 19, 2026, 3:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03ac733e708190a7fde1fb61db5d5f |
completed | May 12, 2026, 10:40 p.m. |
| NEDg | Description generation | batch_6a03ad2be6e0819081426da968a57db0 |
completed | May 12, 2026, 10:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03ad8898748190b57028bb2e2ed207 |
completed | May 12, 2026, 10:45 p.m. |
Created at: April 10, 2026, 10:33 a.m.