Triple
T12207646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fréchet Inception Distance |
E290874
|
entity |
| Predicate | lowerIsBetter |
P11409
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fréchet Inception Distance, lowerIsBetter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowerIsBetter Context triple: [Fréchet Inception Distance, lowerIsBetter, true]
-
A.
lowerValueIndicates
chosen
Indicates that a smaller numerical value of a property or measurement corresponds to a greater degree, better outcome, or stronger presence of the relevant characteristic.
-
B.
lowerRankedOrder
Indicates that one entity holds a lower rank or priority in an ordered sequence relative to another entity.
-
C.
lowerRank
Indicates that one entity holds an inferior or subordinate rank, status, or position relative to another entity.
-
D.
lowestScore
Indicates that the associated value is the smallest (minimum) score among a set of scores.
-
E.
lowestRank
Indicates that the subject has the least or worst rank in an ordered set compared to all other related entities.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.