Triple
T11421681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry Fortensky |
E270635
|
entity |
| Predicate | postMarriageOccupation |
P95303
|
FINISHED |
| Object | continued working in construction intermittently |
—
|
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: continued working in construction intermittently | Statement: [Larry Fortensky, postMarriageOccupation, continued working in construction intermittently]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postMarriageOccupation Context triple: [Larry Fortensky, postMarriageOccupation, continued working in construction intermittently]
-
A.
afterMarriageRole
chosen
Indicates the role or status an entity assumes following a marriage event.
-
B.
spouseOccupation
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
C.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
-
D.
spouseIndustry
Indicates the industry or sector in which a person's spouse is employed or primarily involved.
-
E.
positionOnMarriage
Indicates a person's stance, opinion, or policy regarding the institution or practice of marriage.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801b357e88190ace56d36a945688f |
completed | April 9, 2026, 7:44 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.