Triple
T2988468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe DiMaggio |
E80686
|
entity |
| Predicate | yearsOfMilitaryService |
P44523
|
FINISHED |
| Object | 1943–1945 |
—
|
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: 1943–1945 | Statement: [Joe DiMaggio, yearsOfMilitaryService, 1943–1945]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsOfMilitaryService Context triple: [Joe DiMaggio, yearsOfMilitaryService, 1943–1945]
-
A.
yearsMissedForMilitaryService
Indicates the number of years an entity did not participate in an activity or role due to serving in the military.
-
B.
hasMilitaryServiceStart
Indicates the date or point in time when an entity’s period of military service began.
-
C.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
-
D.
hasMilitaryServiceEnd
Indicates the date or point in time at which an entity’s period of military service concludes.
-
E.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
- F. None of above. chosen
Provenance (4 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c9cdd081908fa8094a3ac1f8d3 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad961403108190bbecb8d3608fd4e0 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:59 p.m.