Triple
T8497012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BSF Artillery Wing |
E201124
|
entity |
| Predicate | primaryMission |
P68
|
FINISHED |
| Object | provide artillery support to BSF formations |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: provide artillery support to BSF formations | Statement: [BSF Artillery Wing, primaryMission, provide artillery support to BSF formations]
Provenance (2 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe57f8c508190b3a93ef180db9873 |
completed | March 31, 2026, 3:17 p.m. |
Created at: March 30, 2026, 6:13 p.m.