Triple
T30577315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hügelland |
E778284
|
entity |
| Predicate | isOftenResultOf |
P170243
|
FINISHED |
| Object | long-term erosion of higher relief |
—
|
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: long-term erosion of higher relief | Statement: [Hügelland, isOftenResultOf, long-term erosion of higher relief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenResultOf Context triple: [Hügelland, isOftenResultOf, long-term erosion of higher relief]
-
A.
isOftenPresentedBy
Indicates that one entity is frequently the agent, host, or medium through which another entity is shown, delivered, or made available.
-
B.
isOftenCalled
Indicates that one entity is frequently referred to or known by the name or label of another entity.
-
C.
isFrequently
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
-
D.
wereOften
Indicates that the related entities frequently or repeatedly exhibited the specified state, behavior, or relationship in the past.
-
E.
isFrequentlyIncludedIn
Indicates that something is regularly or commonly contained or made part of something else.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 8:23 p.m.