Triple
T11923889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpe d’Huez |
E283731
|
entity |
| Predicate | SarenneDescription |
P102171
|
FINISHED |
| Object | one of the longest black runs in the world |
—
|
LITERAL 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: one of the longest black runs in the world | Statement: [Alpe d’Huez, SarenneDescription, one of the longest black runs in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SarenneDescription Context triple: [Alpe d’Huez, SarenneDescription, one of the longest black runs in the world]
-
A.
serpentDescription
Indicates that a description or characterization is being provided for a serpent.
-
B.
sacredRiver
Indicates that a river is regarded as holy or spiritually significant within a religious or cultural tradition.
-
C.
eraDescribed
Indicates that a subject provides a description or characterization of a particular historical or temporal era.
-
D.
southernShore
Indicates that one entity is located along or forms the southern shoreline or coastal edge of another entity.
-
E.
FrenchSide
Indicates that an entity is positioned on, associated with, or belongs to the French side of a border, division, or relationship.
- F. None of above. chosen
Provenance (4 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8e2fc648190a446c1917db1c7d9 |
completed | April 10, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.