Triple
T13918495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umara |
E334681
|
entity |
| Predicate | opposedNumberForm |
P3333
|
FINISHED |
| Object | singular: Amir |
—
|
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: singular: Amir | Statement: [Umara, opposedNumberForm, singular: Amir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedNumberForm Context triple: [Umara, opposedNumberForm, singular: Amir]
-
A.
hasOppositeNumberForm
chosen
Indicates that one entity is represented by a number form that is the opposite (e.g., additive vs. subtractive, positive vs. negative, or otherwise contrastive) of the number form used to represent the other entity.
-
B.
opposedNumberOfTerms
Indicates that two entities are in opposition with respect to the number of terms they involve or are associated with.
-
C.
oppositeNumber
Indicates that one number is the additive inverse of the other, such that their sum equals zero.
-
D.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
E.
opposedOperation
Indicates that one operation is in conflict with, counters, or works against another operation.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de272753e48190bc609482635280ff |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.