Triple
T18610649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shteynberg |
E454881
|
entity |
| Predicate | meaningOfElement_Berg |
P87583
|
FINISHED |
| Object | mountain |
—
|
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: mountain | Statement: [Shteynberg, meaningOfElement_Berg, mountain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningOfElement_Berg Context triple: [Shteynberg, meaningOfElement_Berg, mountain]
-
A.
meaningOfElement_helm
Indicates that one entity represents the meaning, definition, or conceptual interpretation of the element "helm" in relation to another entity.
-
B.
directionFromBern
Indicates the cardinal or relative direction in which one entity is located when measured outward starting from Bern.
-
C.
objectMeaning
Indicates that one entity represents, expresses, or conveys the meaning or semantic content of another entity.
-
D.
hasParticularSignificanceFor
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
E.
FitzElementMeaning
chosen
Indicates a relationship where an element is associated with, or conveys, a particular meaning or interpretive significance.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d013748819099126e27e7ec543d |
completed | April 19, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.