Triple
T15516393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peng-Peng Lee |
E368843
|
entity |
| Predicate | apparatusSpecialty |
P15815
|
FINISHED |
| Object | balance beam |
—
|
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: balance beam | Statement: [Peng-Peng Lee, apparatusSpecialty, balance beam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apparatusSpecialty Context triple: [Peng-Peng Lee, apparatusSpecialty, balance beam]
-
A.
describesApparatus
Indicates that one entity provides a description or specification of an apparatus used by another entity or within a particular context.
-
B.
operationalSpecialty
Indicates a relationship where an entity has a particular area of operational focus, expertise, or functional specialization within its activities or duties.
-
C.
notableGroundEquipment
Indicates that there is ground-based equipment at or associated with an entity that is considered significant or noteworthy in some context.
-
D.
craftType
Indicates the specific kind or category of craft or vessel associated with an entity.
-
E.
ridingSpecialty
chosen
Indicates that one entity has a particular area of expertise or focus related to riding (e.g., a specific riding style, discipline, or type).
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04033303c8190a87b6384f68a6921 |
completed | April 16, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 4:02 a.m.