Triple
T15332177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loen valley |
E366561
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Loelva
Loelva is a river flowing through Norway’s scenic Loen valley, known for its glacial origins and striking turquoise waters.
|
E1151675
|
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: Loelva | Statement: [Loen valley, hasRiver, Loelva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loelva Context triple: [Loen valley, hasRiver, Loelva]
-
A.
Novilara
Novilara is an archaeological site and locality in the Marche region of Italy, known for its ancient Picene culture remains and notable funerary stelae.
-
B.
Freirina
Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
-
C.
Givlaari
Givlaari is an RNA interference-based therapy used to treat acute hepatic porphyria by reducing the production of toxic heme intermediates in the liver.
-
D.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
-
E.
Saravena
Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
- 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: Loelva Triple: [Loen valley, hasRiver, Loelva]
Generated description
Loelva is a river flowing through Norway’s scenic Loen valley, known for its glacial origins and striking turquoise waters.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Loelva Target entity description: Loelva is a river flowing through Norway’s scenic Loen valley, known for its glacial origins and striking turquoise waters.
-
A.
Novilara
Novilara is an archaeological site and locality in the Marche region of Italy, known for its ancient Picene culture remains and notable funerary stelae.
-
B.
Freirina
Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
-
C.
Givlaari
Givlaari is an RNA interference-based therapy used to treat acute hepatic porphyria by reducing the production of toxic heme intermediates in the liver.
-
D.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
-
E.
Saravena
Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01ecb904819082454622dcd77556 |
completed | May 9, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_69ff03d4432c8190af9ce13c0ff70a36 |
completed | May 9, 2026, 9:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff044e01308190b2f077aecae1eece |
completed | May 9, 2026, 9:54 a.m. |
Created at: April 10, 2026, 3:17 a.m.