Triple
T13657780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Arcs |
E326906
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object |
Arc 2000
Arc 2000 is a high-altitude ski resort village in the Les Arcs ski area of the French Alps, known for its extensive slopes and reliable snow conditions.
|
E1052588
|
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: Arc 2000 | Statement: [Les Arcs, hasVillage, Arc 2000]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arc 2000 Context triple: [Les Arcs, hasVillage, Arc 2000]
-
A.
Arcop
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
-
B.
ARC2
ARC2 is a deep learning model architecture designed for efficient and accurate text classification tasks.
-
C.
ARC 700 family
The ARC 700 family is a series of configurable 32-bit embedded processor cores from Synopsys’ ARC architecture line, designed for high-performance, low-power system-on-chip applications.
-
D.
Arcore
Arcore is a small town in the Lombardy region of northern Italy, known for its historic villas and proximity to Milan.
-
E.
The Arc Hammer
The Arc Hammer is a massive Imperial starship and mobile factory in the Star Wars universe, known for producing Dark Troopers in the game Star Wars: Dark Forces.
- 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: Arc 2000 Triple: [Les Arcs, hasVillage, Arc 2000]
Generated description
Arc 2000 is a high-altitude ski resort village in the Les Arcs ski area of the French Alps, known for its extensive slopes and reliable snow conditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arc 2000 Target entity description: Arc 2000 is a high-altitude ski resort village in the Les Arcs ski area of the French Alps, known for its extensive slopes and reliable snow conditions.
-
A.
Arcop
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
-
B.
ARC2
ARC2 is a deep learning model architecture designed for efficient and accurate text classification tasks.
-
C.
ARC 700 family
The ARC 700 family is a series of configurable 32-bit embedded processor cores from Synopsys’ ARC architecture line, designed for high-performance, low-power system-on-chip applications.
-
D.
Arcore
Arcore is a small town in the Lombardy region of northern Italy, known for its historic villas and proximity to Milan.
-
E.
The Arc Hammer
The Arc Hammer is a massive Imperial starship and mobile factory in the Star Wars universe, known for producing Dark Troopers in the game Star Wars: Dark Forces.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc61d56e4819084ae3c16ecdf4a05 |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b06c5d081909d31b8a537c94edb |
completed | May 3, 2026, 5:51 p.m. |
| NEDg | Description generation | batch_69f78bd727048190a57a75294a9ab53d |
completed | May 3, 2026, 5:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78c94da6c8190b9bc1d04cee19c3c |
completed | May 3, 2026, 5:57 p.m. |
Created at: April 9, 2026, 9:52 p.m.