Triple
T14961851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amaya Namani |
E373081
|
entity |
| Predicate | typeOfSoldier |
P6154
|
FINISHED |
| Object | augmented supersoldier |
—
|
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: augmented supersoldier | Statement: [Amaya Namani, typeOfSoldier, augmented supersoldier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSoldier Context triple: [Amaya Namani, typeOfSoldier, augmented supersoldier]
-
A.
soldierCaste
Indicates that an entity belongs to, or is characterized as part of, a soldier or warrior class within a social or organizational hierarchy.
-
B.
typeOfTroops
chosen
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
C.
hasSoldier
Indicates that one entity possesses, employs, or is associated with a soldier or group of soldiers.
-
D.
isRegularArmyUnit
Indicates that the entity functions as a formal, organized military unit within a country's regular (non-irregular) armed forces.
-
E.
militaryPerson
Indicates that the subject is a member of the armed forces or serves in a formal military capacity.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cece6881908cd8c8fe41583bee |
completed | April 15, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:40 a.m.