Triple
T26818435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matuyama reversed chron |
E675179
|
entity |
| Predicate | polarityRelativeToPresent |
P138082
|
FINISHED |
| Object | opposite |
—
|
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: opposite | Statement: [Matuyama reversed chron, polarityRelativeToPresent, opposite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: polarityRelativeToPresent Context triple: [Matuyama reversed chron, polarityRelativeToPresent, opposite]
-
A.
polarity
Indicates whether the relationship or statement is affirmed (positive) or denied/opposed (negative).
-
B.
directionRelativeTo
Indicates the spatial orientation of one entity in relation to another, such as which way it faces or points relative to a reference entity.
-
C.
relativePosition
Indicates the spatial relationship of one entity’s location with respect to another entity’s position.
-
D.
associatedWithPolarity
chosen
Indicates a relationship where one entity is linked to, characterized by, or carries a specific polarity (such as positive, negative, or neutral) in relation to another entity or context.
-
E.
relativePositioning
Indicates how one entity is spatially arranged or located in relation to another entity.
- 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_69eee9b6b28481909332f83eb17e5170 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61a87b34081909f7e7276e9e9c82b |
completed | May 2, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:53 a.m.