Triple
T35384238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shooter (novel) |
E1022738
|
entity |
| Predicate | featuresMilitaryBackgroundOfProtagonist |
P92729
|
FINISHED |
| Object | United States Marine Corps |
E892
|
NE 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: United States Marine Corps | Statement: [Shooter (novel), featuresMilitaryBackgroundOfProtagonist, United States Marine Corps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMilitaryBackgroundOfProtagonist Context triple: [Shooter (novel), featuresMilitaryBackgroundOfProtagonist, United States Marine Corps]
-
A.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
B.
militaryCharacteristic
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
-
C.
mainCharacterMilitaryService
chosen
Indicates that the main character has served or is serving in the military, capturing their involvement in formal armed forces service.
-
D.
hadMilitaryFollowing
Indicates that an entity was supported or backed by a group of military personnel or forces.
-
E.
militaryConflictInBackstory
Indicates that a character or entity has a history involving a military conflict that occurred prior to the main events or timeline being described.
- F. None of above.
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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a382cc00f48819090a20c44782cc1f9 |
completed | June 21, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.