Triple
T19100046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pointe Walker |
E467507
|
entity |
| Predicate | firstAscentBy |
P1321
|
FINISHED |
| Object | Julien Grange |
—
|
NE NERFINISHED |
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: Julien Grange | Statement: [Pointe Walker, firstAscentBy, Julien Grange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julien Grange Context triple: [Pointe Walker, firstAscentBy, Julien Grange]
-
A.
Julien Grange
chosen
Julien Grange was a mountaineer known for participating in the pioneering first ascent of the Grandes Jorasses in the Mont Blanc massif.
-
B.
Romain Grange
Romain Grange is a French professional footballer known for playing as a midfielder in the French football leagues.
-
C.
Clément Delangue
Clément Delangue is a French entrepreneur and CEO best known for co-founding Hugging Face, a leading company in open-source artificial intelligence and natural language processing.
-
D.
Loïc Le Meur
Loïc Le Meur is a French entrepreneur and blogger best known as the founder of the LeWeb technology conference and for his involvement in multiple internet startups.
-
E.
Antoine Bourseiller
Antoine Bourseiller was a French actor and theater director known for his work in mid-20th-century French cinema and stage productions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36d279081908aeb472cd740c302 |
completed | April 20, 2026, 8:27 a.m. |
Created at: April 10, 2026, 12:04 p.m.