Triple
T12535549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Round Mound of Rebound |
E299679
|
entity |
| Predicate | describesPhysicalTraits |
P62520
|
FINISHED |
| Object | stocky frame |
—
|
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: stocky frame | Statement: [The Round Mound of Rebound, describesPhysicalTraits, stocky frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesPhysicalTraits Context triple: [The Round Mound of Rebound, describesPhysicalTraits, stocky frame]
-
A.
physicalCharacteristics
chosen
Indicates that one entity has or describes the bodily or material attributes, features, or appearance of another entity.
-
B.
hasPhysicalFeature
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
-
C.
biologicalCharacteristic
Indicates that one entity possesses or exhibits a particular biological trait, feature, or property in relation to another.
-
D.
fleshCharacteristic
Indicates that one entity has a particular property, quality, or attribute of its flesh (such as texture, color, or condition) in relation to another entity or value.
-
E.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.