Triple
T11836683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Louw |
E281534
|
entity |
| Predicate | careerPeriod |
P18004
|
FINISHED |
| Object | late 20th century |
—
|
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: late 20th century | Statement: [John Louw, careerPeriod, late 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerPeriod Context triple: [John Louw, careerPeriod, late 20th century]
-
A.
careerSeasons
Indicates the number or set of seasons during which an entity actively participated in a particular career or professional role.
-
B.
activeYearsInCareer
chosen
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
C.
hasCareerSpanCoverage
Indicates that one entity’s coverage, record, or data extends across the full duration of another entity’s career span.
-
D.
activeYearsInSport
Indicates the span of years during which an entity actively participated in a particular sport.
-
E.
refersToEraOfCareer
Indicates that one entity specifies or denotes the particular era or phase within another entity’s career.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62fec0881908c7b89c0b5bcc9a2 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.