Triple
T1422250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OWL Full |
E30248
|
entity |
| Predicate | hasTradeoff |
P28908
|
FINISHED |
| Object | expressivity versus decidability |
—
|
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: expressivity versus decidability | Statement: [OWL Full, hasTradeoff, expressivity versus decidability]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTradeoff Context triple: [OWL Full, hasTradeoff, expressivity versus decidability]
-
A.
hasTrade
Indicates a relationship where one entity engages in or maintains a commercial exchange or trading activity with another entity.
-
B.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
C.
compromiseFeature
Indicates that one entity weakens, reduces, or negatively affects the quality, effectiveness, or integrity of a feature of another entity.
-
D.
hasNotableInterchange
Indicates that there exists a significant or well-known point of exchange, connection, or transfer between the related entities.
-
E.
hasOpposingFront
Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
- F. None of above. chosen
Provenance (4 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8 p.m.