Triple
T7689442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victory Program |
E174207
|
entity |
| Predicate | estimatedForces |
P61382
|
FINISHED |
| Object | multi-million man U.S. Army |
—
|
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: multi-million man U.S. Army | Statement: [Victory Program, estimatedForces, multi-million man U.S. Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedForces Context triple: [Victory Program, estimatedForces, multi-million man U.S. Army]
-
A.
engagedForces
Indicates that one force has actively committed or deployed its military units against another force in combat or operational interaction.
-
B.
attackingForceApprox
chosen
Indicates that one entity is the approximate attacking force, in terms of size or strength, relative to another entity or context.
-
C.
strengthGovernmentForces
Indicates the level or degree of military or coercive power held or exerted by government forces in a given context.
-
D.
besiegingForce
Indicates a military group that is surrounding and attacking a target location or force in an attempt to capture or subdue it.
-
E.
commandingForce2Strength
Indicates that a commanding force possesses or exerts a particular level or measure of strength.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.