Triple
T528336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ville Peltonen |
E10972
|
entity |
| Predicate | laterWorkedAs |
P4325
|
FINISHED |
| Object | head coach in professional ice hockey |
—
|
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: head coach in professional ice hockey | Statement: [Ville Peltonen, laterWorkedAs, head coach in professional ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterWorkedAs Context triple: [Ville Peltonen, laterWorkedAs, head coach in professional ice hockey]
-
A.
workedAs
chosen
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
B.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
C.
workedUnder
Indicates that one entity was hierarchically subordinate to and performed work under the supervision or authority of another entity.
-
D.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
-
E.
associatedWork
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d39b4c81909f265b3501b5ec1d |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f01ac3ec8190a94a05955532c7fa |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.