Triple
T37128889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Templeton |
E919461
|
entity |
| Predicate | occupationInAdultTimeline |
P124309
|
FINISHED |
| Object | stay-at-home dad |
—
|
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: stay-at-home dad | Statement: [Tim Templeton, occupationInAdultTimeline, stay-at-home dad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationInAdultTimeline Context triple: [Tim Templeton, occupationInAdultTimeline, stay-at-home dad]
-
A.
adultTimeline
Indicates a temporal relationship capturing events, states, or milestones that occur during an entity’s adult stage or period of adulthood.
-
B.
timeOfMainOccupation
chosen
Indicates the specific time period during which an entity primarily carries out its main occupation or activity.
-
C.
laterOccupationApproxDate
Indicates an approximate date or time period when a subject began a subsequent occupation or role after an earlier one.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
hasAdultLifeIn
Indicates that an entity spends or experiences its adult stage of life within a specified location or environment.
- 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:15 p.m.