Triple
T36555263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arda Marred |
E901681
|
entity |
| Predicate | hasOppositeState |
P77967
|
FINISHED |
| Object | Arda Unmarred |
—
|
NE NERFINISHED |
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: Arda Unmarred | Statement: [Arda Marred, hasOppositeState, Arda Unmarred]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOppositeState Context triple: [Arda Marred, hasOppositeState, Arda Unmarred]
-
A.
hasOppositeStatus
chosen
Indicates that two entities hold directly contrasting or mutually exclusive statuses within a given context.
-
B.
hasOppositeComponent
Indicates that one component is related to another as its opposite or contrasting counterpart within a system or structure.
-
C.
hasOppositeView
Indicates that one entity holds a view or opinion that is directly opposed to that of another entity.
-
D.
hasOppositeStructure
Indicates that one entity possesses a structure that is the inverse or opposite in form, arrangement, or organization relative to another entity.
-
E.
hasOppositeTime
Indicates a temporal relationship where one time point or period is positioned as the direct opposite or inverse of another within a defined temporal framework (e.g., day vs. night, past vs. future).
- 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_69f76e634e9481908c9ba1b87ab87c26 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
Created at: May 3, 2026, 4:11 p.m.