Triple
T13350158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014–2015 USS Theodore Roosevelt incidents |
E318047
|
entity |
| Predicate | phenomenaCharacteristic |
P662
|
FINISHED |
| Object | high speed |
—
|
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: high speed | Statement: [2014–2015 USS Theodore Roosevelt incidents, phenomenaCharacteristic, high speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: phenomenaCharacteristic Context triple: [2014–2015 USS Theodore Roosevelt incidents, phenomenaCharacteristic, high speed]
-
A.
phenomenon
Indicates that an entity is a perceptible event, occurrence, or process that can be observed or experienced.
-
B.
capturesPhenomenon
Indicates that one entity records, represents, or effectively reflects the occurrence or characteristics of a particular phenomenon.
-
C.
themeCharacteristic
Indicates that a characteristic, quality, or property is attributed to or associated with a particular theme.
-
D.
affectsPhenomenon
Indicates that one phenomenon produces an influence or change on another phenomenon.
-
E.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.