Triple
T29924642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Boyd |
E760043
|
entity |
| Predicate | servedYears |
P46479
|
FINISHED |
| Object | 1951–1975 |
—
|
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: 1951–1975 | Statement: [John Boyd, servedYears, 1951–1975]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedYears Context triple: [John Boyd, servedYears, 1951–1975]
-
A.
yearsOfMilitaryService
Indicates the number of years an entity has served or is recorded as serving in the military.
-
B.
servesYears
Indicates the duration, measured in years, that an entity performs a particular role, service, or function.
-
C.
serviceNumberOrYearsOfService
Indicates a relationship that specifies either an entity’s service identification number or the duration of time the entity has served.
-
D.
militaryServicePeriod
chosen
Indicates the span of time during which an entity serves or has served in a military capacity.
-
E.
hasTimePeriodOfService
Indicates that an entity is associated with a specific span of time during which it provided service or was actively serving.
- 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_69f224631674819080c8d089674f9f4f |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fe5c1a502081909d4024e514309c8e |
completed | May 8, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69fe5a9df21c819087153f5d0bcaa987 |
completed | May 8, 2026, 9:50 p.m. |
Created at: April 29, 2026, 6:15 p.m.