Triple
T2740805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnny Pesky |
E60743
|
entity |
| Predicate | yearsMissedForMilitaryService |
P41774
|
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: [Johnny Pesky, yearsMissedForMilitaryService, 1943-1945]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsMissedForMilitaryService Context triple: [Johnny Pesky, yearsMissedForMilitaryService, 1943-1945]
-
A.
hasMilitaryServiceEnd
Indicates the date or point in time at which an entity’s period of military service concludes.
-
B.
militaryStatus
Indicates the relationship between an entity and a military organization in terms of service condition, such as active duty, reserve, veteran, or non-military status.
-
C.
hasMilitaryServiceStart
Indicates the date or point in time when an entity’s period of military service began.
-
D.
ageAtEnlistment
Indicates the age a person was when they enlisted in a service, organization, or role.
-
E.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb2f210881909126307cc92ebfef |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd968b2148190929af432c9d8001f |
completed | March 7, 2026, 7:53 a.m. |
Created at: March 6, 2026, 9:56 p.m.