Triple
T18610650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shteynberg |
E454881
|
entity |
| Predicate | hasApproximateMeaning |
P81437
|
FINISHED |
| Object | stone 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: stone mountain | Statement: [Shteynberg, hasApproximateMeaning, stone mountain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateMeaning Context triple: [Shteynberg, hasApproximateMeaning, stone mountain]
-
A.
literalMeaningApproximation
chosen
Indicates that one entity expresses an approximate or rough literal meaning of another entity, rather than an exact or fully precise interpretation.
-
B.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
C.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
D.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
E.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
- 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.