Triple
T14527745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'll Make a Man Out of You |
E340822
|
entity |
| Predicate | usesAsSetting |
P15599
|
FINISHED |
| Object | military training camp |
—
|
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: military training camp | Statement: [I'll Make a Man Out of You, usesAsSetting, military training camp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAsSetting Context triple: [I'll Make a Man Out of You, usesAsSetting, military training camp]
-
A.
usedAsSettingFor
chosen
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
B.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
C.
associatedWithSetting
Indicates that one entity is connected or linked to a particular context, environment, or setting in which it occurs or is relevant.
-
D.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
E.
basedOnSetting
Indicates that one entity is derived from, influenced by, or constructed using the setting or contextual environment defined by another entity.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea051bc608190ad4d516c5e7bca43 |
completed | April 14, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:22 a.m.