Triple
T20128263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell County |
E490814
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Vars
Vars is a small community located within Russell County in the Canadian province of Ontario.
|
E1412443
|
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: Vars | Statement: [Russell County, containsSettlement, Vars]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vars Context triple: [Russell County, containsSettlement, Vars]
-
A.
Vars
Vars is a French alpine commune and ski resort village located in the Hautes-Alpes department in southeastern France.
-
B.
Var
Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
-
C.
Var
Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
-
D.
VAR
VAR (Video Assistant Referee) is a football officiating system that uses video technology to help referees review and correct clear and obvious errors in key match situations.
-
E.
VAR
VAR is the three-letter IATA airport code assigned to Varna Airport in Varna, Bulgaria.
- 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: Vars Triple: [Russell County, containsSettlement, Vars]
Generated description
Vars is a small community located within Russell County in the Canadian province of Ontario.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vars Target entity description: Vars is a small community located within Russell County in the Canadian province of Ontario.
-
A.
Vars
Vars is a French alpine commune and ski resort village located in the Hautes-Alpes department in southeastern France.
-
B.
Var
Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
-
C.
Var
Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
-
D.
VAR
VAR (Video Assistant Referee) is a football officiating system that uses video technology to help referees review and correct clear and obvious errors in key match situations.
-
E.
VAR
VAR is the three-letter IATA airport code assigned to Varna Airport in Varna, Bulgaria.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6675fe3d48190b0c20b483a951e68 |
completed | April 20, 2026, 5:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a082ddbae5481908ee89666afa6296e |
completed | May 16, 2026, 8:42 a.m. |
| NEDg | Description generation | batch_6a082ed267588190ac209a5f5fcdac16 |
completed | May 16, 2026, 8:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a082f5360ac8190bdfe653cb48c6ecb |
completed | May 16, 2026, 8:48 a.m. |
Created at: April 11, 2026, 11:31 p.m.