Triple
T34891949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Colonel Nathaniel Serling |
E1006309
|
entity |
| Predicate | associatedAwardInvestigation |
—
|
GENERATED |
| Object | Medal of Honor |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAwardInvestigation Context triple: [Lieutenant Colonel Nathaniel Serling, associatedAwardInvestigation, Medal of Honor]
-
A.
investigatedBy
Indicates that an entity is the subject of an investigation carried out by another entity.
-
B.
relatedAward
chosen
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
-
C.
investigationInvolvement
Indicates that an entity participates in, is associated with, or plays a role in a particular investigation.
-
D.
relatedInvestigationOf
Indicates that one investigation is connected to, derived from, or concerned with another investigation or case.
-
E.
investigatesIn
Indicates that an entity conducts an investigation or inquiry within, or focused on, a particular context, location, or domain.
- F. None of above.
Provenance (1 batch)
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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4 p.m.