Triple
T6968954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dasara in Mysuru |
E161554
|
entity |
| Predicate | featuresUnit |
P17143
|
FINISHED |
| Object | Mounted police |
—
|
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: Mounted police | Statement: [Dasara in Mysuru, featuresUnit, Mounted police]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresUnit Context triple: [Dasara in Mysuru, featuresUnit, Mounted police]
-
A.
featuredUnitType
Indicates that a particular unit type is highlighted or given special prominence relative to other unit types.
-
B.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
C.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
D.
featuresItem
Indicates that one entity includes, presents, or highlights another entity as a notable item or component.
-
E.
featuresGroup
chosen
Indicates that an entity includes or is associated with a specific group as one of its features or components.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db152b2081909271493a5d1469fb |
completed | March 27, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:30 p.m.