Triple
T11923908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpe d’Huez |
E283731
|
entity |
| Predicate | hairpinsNumberedFrom |
P102173
|
FINISHED |
| Object | 1 at the top to 21 at the bottom |
—
|
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: 1 at the top to 21 at the bottom | Statement: [Alpe d’Huez, hairpinsNumberedFrom, 1 at the top to 21 at the bottom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairpinsNumberedFrom Context triple: [Alpe d’Huez, hairpinsNumberedFrom, 1 at the top to 21 at the bottom]
-
A.
hasNumberOfPins
Indicates that an entity is associated with a specific count of pins it possesses or uses.
-
B.
pillarNumber
Indicates the specific numerical identifier assigned to a particular pillar within a set or structure.
-
C.
arrowCount
Indicates the number of arrows associated with or involved in a given entity or interaction.
-
D.
hornCount
Indicates the number of horns possessed by an entity.
-
E.
hasHairpinBends
Indicates that a route, road, or path includes very sharp, U-shaped turns resembling hairpins.
- 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.