Triple
T1117619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhône Glacier |
E11136
|
entity |
| Predicate | hasManMadeStructure |
P1495
|
FINISHED |
| Object | ice grotto tunnel |
—
|
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: ice grotto tunnel | Statement: [Rhône Glacier, hasManMadeStructure, ice grotto tunnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManMadeStructure Context triple: [Rhône Glacier, hasManMadeStructure, ice grotto tunnel]
-
A.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
B.
isMostDistantHumanMadeObject
Indicates that the subject is the human-made object currently farthest from Earth (or from its point of origin).
-
C.
hasTouristInfrastructure
Indicates that a place is equipped with facilities and services designed to support and accommodate tourists.
-
D.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
hasUrbanFeature
chosen
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
- F. None of above.
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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4562f48190831e959f5f309956 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.