Triple
T30956707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio 2016 Olympic Torch Relay |
E788694
|
entity |
| Predicate | torchFeatures |
P171321
|
FINISHED |
| Object | expanding segments revealing colors of the Brazilian flag |
—
|
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: expanding segments revealing colors of the Brazilian flag | Statement: [Rio 2016 Olympic Torch Relay, torchFeatures, expanding segments revealing colors of the Brazilian flag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: torchFeatures Context triple: [Rio 2016 Olympic Torch Relay, torchFeatures, expanding segments revealing colors of the Brazilian flag]
-
A.
trainFeature
Indicates that an entity is a characteristic, capability, or attribute associated with a train.
-
B.
sharesFeatureExtractor
Indicates that two or more models or components use the same feature extraction mechanism or module.
-
C.
torchName
Indicates that a torch is identified or labeled by a specific name.
-
D.
featuresTransformationOf
Indicates that something includes or presents a transformation or change applied to another entity.
-
E.
torchType
Indicates the specific kind or category of torch associated with an 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69dfbf6ac8190ba2e6fc0adfd8b73 |
completed | May 3, 2026, 12:59 a.m. |
Created at: April 29, 2026, 8:54 p.m.