Triple
T234877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Armstrong |
E4486
|
entity |
| Predicate | turnedProfessionalIn |
P4697
|
FINISHED |
| Object | 1931 |
—
|
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: 1931 | Statement: [Henry Armstrong, turnedProfessionalIn, 1931]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnedProfessionalIn Context triple: [Henry Armstrong, turnedProfessionalIn, 1931]
-
A.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
B.
workBecame
Indicates that one work was transformed, adapted, or evolved into another work over time.
-
C.
isAmateur
Indicates that an entity engages in an activity or field on a non-professional, typically unpaid or hobbyist basis.
-
D.
occupationBegan
chosen
Indicates the point in time when an entity started holding a particular occupation or job.
-
E.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25cc9ab2c81909af278a07f86aa1e |
completed | Feb. 28, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69a25b5dc640819092669575731c393f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.