Triple
T1302328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ati Vishisht Seva Medal |
E27793
|
entity |
| Predicate | orderOfWearInIndia |
P6168
|
FINISHED |
| Object | below Param Vishisht Seva Medal |
—
|
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: below Param Vishisht Seva Medal | Statement: [Ati Vishisht Seva Medal, orderOfWearInIndia, below Param Vishisht Seva Medal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderOfWearInIndia Context triple: [Ati Vishisht Seva Medal, orderOfWearInIndia, below Param Vishisht Seva Medal]
-
A.
orderOfWearInUK
Indicates the sequence or priority in which items are worn in the UK context (e.g., clothing or insignia), relative to other items.
-
B.
wearingOrder
Indicates the relative sequence in which items are worn on or over one another (e.g., which garment is worn over or under another).
-
C.
orderPrecedenceWithinIndia
chosen
Indicates the relative ranking or priority of entities in terms of legal or administrative precedence within the jurisdiction of India.
-
D.
rankByLengthInIndia
Indicates an ordering of items based on their length specifically within the context or boundaries of India.
-
E.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c115ba64819081c55fa6807e19ef |
completed | March 1, 2026, 10:43 p.m. |
| PD | Predicate disambiguation | batch_69a4bee8544c8190874efd9bae9bccf9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.