Triple
T28714482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Petrova / Alexei Tikhonov |
E729919
|
entity |
| Predicate | hasSkater |
P165253
|
FINISHED |
| Object | Maria Petrova |
—
|
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: Maria Petrova | Statement: [Maria Petrova / Alexei Tikhonov, hasSkater, Maria Petrova]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSkater Context triple: [Maria Petrova / Alexei Tikhonov, hasSkater, Maria Petrova]
-
A.
ageOfSkater
Indicates the numerical age associated with a given skater.
-
B.
hasAthlete
Indicates a relationship where an entity (such as a team, organization, or event) includes or is associated with one or more athletes.
-
C.
hasFreeSkateSegment
Indicates that an entity includes or is associated with a free skate segment within a skating program or competition.
-
D.
playsOnRinkType
Indicates that an entity participates in a game or activity on a specific type of rink surface or rink configuration.
-
E.
hasIceArena
Indicates that one entity possesses, contains, or includes an ice arena as a facility or feature.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 5:50 a.m.