Triple
T29037467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The British School, New Delhi |
E737901
|
entity |
| Predicate | offersEnvironment |
P9404
|
FINISHED |
| Object | multicultural learning environment |
—
|
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: multicultural learning environment | Statement: [The British School, New Delhi, offersEnvironment, multicultural learning environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersEnvironment Context triple: [The British School, New Delhi, offersEnvironment, multicultural learning environment]
-
A.
offersServiceIn
Indicates that a provider makes a particular service available within a specified location or jurisdiction.
-
B.
offersObject
Indicates that a subject provides or makes available a specific object to another party as an offer.
-
C.
offersDesktopEnvironment
Indicates that one entity provides or makes available a desktop environment for another entity to use.
-
D.
offersFeature
chosen
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
E.
offersInterface
Indicates that one entity provides or exposes a specific interface that another entity can use or interact with.
- 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_69f077efb3848190b41574e1670f6ae2 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: April 28, 2026, 9:59 a.m.