Triple
T37716297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speed |
E939459
|
entity |
| Predicate | hasPowerSetSimilarTo |
P192211
|
FINISHED |
| Object | Quicksilver |
—
|
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: Quicksilver | Statement: [Speed, hasPowerSetSimilarTo, Quicksilver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPowerSetSimilarTo Context triple: [Speed, hasPowerSetSimilarTo, Quicksilver]
-
A.
hasPowerSimilarTo
chosen
Indicates that one entity possesses a level or type of power comparable to that of another entity.
-
B.
hasSimilarityTo
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
C.
hasCommonSubsetSize
Indicates that two sets share at least one subset whose size (number of elements) is the same for both.
-
D.
hasLetterSetSimilarity
Indicates that two entities share a similar set of letters, typically based on overlap or resemblance between the characters in their textual representations.
-
E.
hasRightsSimilarTo
Indicates that one entity possesses rights that are comparable or equivalent in scope or nature to those held by another entity.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffcb5536d88190bfc2e00b854cacfb |
completed | May 10, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69ffc900c2a081909dea04aa60566923 |
completed | May 9, 2026, 11:53 p.m. |
Created at: May 3, 2026, 4:18 p.m.