Triple
T13765419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AS365 Dauphin |
E330728
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | AS365 N1 |
E1058574
|
NE FINISHED |
How this triple was built (2 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: AS365 N1 | Statement: [AS365 Dauphin, hasVariant, AS365 N1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AS365 N1 Context triple: [AS365 Dauphin, hasVariant, AS365 N1]
-
A.
AS365 N
chosen
The AS365 N is a variant of the Eurocopter (now Airbus Helicopters) Dauphin series, a twin-engine medium utility helicopter widely used for search and rescue, offshore transport, and law enforcement operations.
-
B.
N-65
N-65 is a national highway in Pakistan that serves as an important east–west route connecting key cities and regions within the country’s road network.
-
C.
N363
N363 is a regional road in the Netherlands that connects the village of Usquert with other nearby towns in the province of Groningen.
-
D.
N366
N366 is a regional road in the Netherlands that serves as a key connection route for traffic to and from the municipality of Pekela in the province of Groningen.
-
E.
N106
N106 is a French national road that serves as a key route connecting the town of Alès to other parts of southern France.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de022690ac8190bd5410ecc659a2a7 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0724ab481908448d71a1bd02253 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:10 p.m.