Triple
T5898673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aiguille de Bionnassay |
E131164
|
entity |
| Predicate | offersViewOf |
P3821
|
FINISHED |
| Object | Val Veny |
E70462
|
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: Val Veny | Statement: [Aiguille de Bionnassay, offersViewOf, Val Veny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Val Veny Context triple: [Aiguille de Bionnassay, offersViewOf, Val Veny]
-
A.
Val Veny
chosen
Val Veny is a scenic alpine valley near Courmayeur in Italy’s Aosta Valley, known for its dramatic views of Mont Blanc, hiking trails, and natural landscapes.
-
B.
Vanney
Vanney is the surname of Greg Vanney, a former American soccer player and current professional soccer coach.
-
C.
Val Venosta
Val Venosta is a valley in South Tyrol in northern Italy, known for its alpine landscapes, apple orchards, and mix of Italian and German-speaking culture.
-
D.
Valentano
Valentano is a small historic town in the Lazio region of central Italy, known for its medieval architecture and ties to the Farnese noble family.
-
E.
Ramponio Verna
Ramponio Verna is a small Italian municipality in the Lombardy region, situated in the mountainous area near Lake Como and the Swiss border.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036f7b3f48190a499d43f8ffb2fa7 |
completed | March 22, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b15df86481908b59717b9de63655 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.