Triple
T36757928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Cahill |
E908106
|
entity |
| Predicate | militaryStatusInStory |
P65983
|
FINISHED |
| Object | U.S. Marine officer |
—
|
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: U.S. Marine officer | Statement: [Sam Cahill, militaryStatusInStory, U.S. Marine officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryStatusInStory Context triple: [Sam Cahill, militaryStatusInStory, U.S. Marine officer]
-
A.
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.
-
B.
hasMilitaryStatus
chosen
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
-
C.
militaryStatusChange
Indicates a change in an entity’s military status, such as entering, leaving, or transitioning between roles or service conditions within the armed forces.
-
D.
mainCharacterMilitaryService
Indicates that the main character has served or is serving in the military, capturing their involvement in formal armed forces service.
-
E.
hasMilitaryText
Indicates that an entity possesses or is associated with a text whose content is military in nature (e.g., about armed forces, warfare, or defense).
- 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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 3, 2026, 4:12 p.m.