Triple
T13574777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob |
E324251
|
entity |
| Predicate | yearsOfServiceForRachel |
P44523
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Jacob, yearsOfServiceForRachel, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsOfServiceForRachel Context triple: [Jacob, yearsOfServiceForRachel, 14]
-
A.
serviceNumberOrYearsOfService
Indicates a relationship that specifies either an entity’s service identification number or the duration of time the entity has served.
-
B.
hasTimePeriodOfService
Indicates that an entity is associated with a specific span of time during which it provided service or was actively serving.
-
C.
yearsOfMilitaryService
chosen
Indicates the number of years an entity has served or is recorded as serving in the military.
-
D.
managedYearsWithRangers
Indicates the span of years during which an entity held a managerial role with the Rangers organization.
-
E.
periodOfRAFService
Indicates the time span during which an entity served in the Royal Air Force (RAF).
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02b1f108190a12af382d1de70bb |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.