Triple
T25691681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | III Corps (India) |
E644216
|
entity |
| Predicate | languageOfCommandAndControl |
P6537
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [III Corps (India), languageOfCommandAndControl, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCommandAndControl Context triple: [III Corps (India), languageOfCommandAndControl, English]
-
A.
languageOfCommand
chosen
Indicates that a specified language is the one in which a given command is expressed or issued.
-
B.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
C.
languageOfInstructions
Indicates that one entity specifies the language in which instructions or guidance are provided for another entity.
-
D.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or context.
-
E.
combatantLanguage
Indicates the language used by a combatant in a conflict or competitive interaction.
- 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_69e77e82c9bc8190893090b2f6c64f1d |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 21, 2026, 8:28 p.m.