Triple
T31152055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wheelwright |
E794100
|
entity |
| Predicate | childhoodTimePeriod |
P114395
|
FINISHED |
| Object | 1950s and 1960s |
—
|
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: 1950s and 1960s | Statement: [John Wheelwright, childhoodTimePeriod, 1950s and 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childhoodTimePeriod Context triple: [John Wheelwright, childhoodTimePeriod, 1950s and 1960s]
-
A.
timePeriodOfChildhood
chosen
Indicates the span of time during which an entity is considered to have been in its childhood phase.
-
B.
spentChildhoodIn
Indicates that a person or entity spent the majority or formative years of their childhood in a particular place or location.
-
C.
childhoodAssociation
Indicates a relationship where two entities are connected through shared experiences, interactions, or familiarity originating from their childhood period.
-
D.
playedEarlyYearsOf
Indicates that one entity portrayed or acted as the younger/early-life version of another entity in a performance or production.
-
E.
depictsLifePeriod
Indicates that one entity visually represents or portrays a specific period or phase in the life of another entity.
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a0ea04888190ac3a813b603bcb5c |
completed | May 3, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:06 p.m.