Triple
T25294158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dandayudhapani Swamy |
E634169
|
entity |
| Predicate | isAssociatedWithWeapon |
P33241
|
FINISHED |
| Object | staff |
—
|
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: staff | Statement: [Dandayudhapani Swamy, isAssociatedWithWeapon, staff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAssociatedWithWeapon Context triple: [Dandayudhapani Swamy, isAssociatedWithWeapon, staff]
-
A.
associatedWithWeapon
chosen
Indicates that an entity has a connection or involvement with a weapon, such as ownership, use, presence, or relevance in a given context.
-
B.
armedBy
Indicates that one entity is supplied with weapons, equipment, or armaments by another entity.
-
C.
usedWeapon
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
-
D.
weaponSystemAssociatedWith
Indicates that one entity is functionally or organizationally connected to a particular weapon system, such as by using, supporting, or being part of that system.
-
E.
weaponForgedFor
Indicates that a weapon was specifically created or crafted for a particular entity, purpose, or context.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48fd007388190a7d80ea457119072 |
completed | May 1, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:22 p.m.