Triple
T14522800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mussoorie International School |
E340693
|
entity |
| Predicate | hasScienceLaboratories |
P113085
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mussoorie International School, hasScienceLaboratories, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScienceLaboratories Context triple: [Mussoorie International School, hasScienceLaboratories, yes]
-
A.
hasResearchInfrastructure
Indicates that an entity possesses, controls, or provides access to facilities, equipment, or resources used to conduct research.
-
B.
hasLaboratorySpace
chosen
Indicates that an entity provides or contains designated laboratory facilities or areas for scientific or technical work.
-
C.
relatedLaboratory
Indicates that one entity has an associated or connected laboratory, such as a facility used for its research, testing, or experimental activities.
-
D.
hasScienceCenter
Indicates that an entity possesses, hosts, or includes a science center as one of its facilities or components.
-
E.
hasResearchCenters
Indicates that an entity possesses, hosts, or is associated with one or more research centers.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea04f16f88190ba357b0f8021b46b |
completed | April 14, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:22 a.m.