Triple
T4298509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aletsch Glacier |
E99774
|
entity |
| Predicate | hasMaximumThickness |
P55323
|
FINISHED |
| Object | over 800 meters |
—
|
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: over 800 meters | Statement: [Aletsch Glacier, hasMaximumThickness, over 800 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumThickness Context triple: [Aletsch Glacier, hasMaximumThickness, over 800 meters]
-
A.
armorThicknessMax
Indicates the maximum thickness of armor that an entity possesses or can withstand.
-
B.
hasMaximumDepth
Indicates that an entity possesses a greatest or limiting depth value beyond which it does not extend.
-
C.
hasMaximumValue
Indicates that one value in a set is the greatest or highest possible according to a specified criterion.
-
D.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
E.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509d39348190aa83304661230cba |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:08 p.m.