Triple
T26818468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C2r |
E675180
|
entity |
| Predicate | hasPolarityType |
P138082
|
FINISHED |
| Object | reversed chron |
—
|
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: reversed chron | Statement: [C2r, hasPolarityType, reversed chron]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolarityType Context triple: [C2r, hasPolarityType, reversed chron]
-
A.
hasPolarityPattern
Indicates a relationship where an entity exhibits a specific configuration or pattern of positive and negative polarity across its components or features.
-
B.
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.
-
C.
logicalPolarity
Indicates that the truth value of a statement is affirmed (positive) or denied (negative) relative to some logical context.
-
D.
polarizationLevel
Indicates the degree or intensity of polarization present in a given context, such as between opinions, groups, or signals.
-
E.
polarity
Indicates whether the relationship or statement is affirmed (positive) or denied/opposed (negative).
- 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_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 27, 2026, 4:53 a.m.