Triple
T26703335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wardell Pomeroy in Kinsey |
E673218
|
entity |
| Predicate | timePeriodOfActivityInWork |
P7950
|
FINISHED |
| Object | mid-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: mid-20th century | Statement: [Wardell Pomeroy in Kinsey, timePeriodOfActivityInWork, mid-20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfActivityInWork Context triple: [Wardell Pomeroy in Kinsey, timePeriodOfActivityInWork, mid-20th century]
-
A.
timePeriodOfWorks
Indicates the span of time during which the associated works were created, produced, or active.
-
B.
workPeriod
chosen
Indicates the span of time during which an entity is engaged in a particular work or employment activity.
-
C.
workLength
Indicates the duration or length of time associated with a particular work or task.
-
D.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
-
E.
workSettingPeriod
Indicates the time period during which a particular work setting or employment context is in effect.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 27, 2026, 3:32 a.m.