Triple
T552934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zdeno Chára |
E11879
|
entity |
| Predicate | retiredFromProfessionalPlay |
P2089
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Zdeno Chára, retiredFromProfessionalPlay, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: retiredFromProfessionalPlay Context triple: [Zdeno Chára, retiredFromProfessionalPlay, true]
-
A.
retiredFrom
Indicates that an entity has permanently stopped working for or being active in a specified organization, role, or activity.
-
B.
retired
chosen
Indicates that an entity has permanently stopped working in their former occupation or role, typically after reaching a certain age or service duration.
-
C.
spentEntireMLBCareerWith
Indicates that a player spent their entire Major League Baseball career with a single team.
-
D.
formerWorldNo1
Indicates that the subject was ranked number one in the world in the past, but does not hold that top ranking currently.
-
E.
retiredNumber
Indicates that an entity (typically a team or organization) has formally withdrawn a specific number from future use, usually to honor a particular individual or achievement associated with that number.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991b296481908cf27e1d1ec67052 |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bc1f8c8190904356f3a8e801de |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.