Triple
T14522801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mussoorie International School |
E340693
|
entity |
| Predicate | hasComputerLaboratories |
P40186
|
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, hasComputerLaboratories, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComputerLaboratories Context triple: [Mussoorie International School, hasComputerLaboratories, yes]
-
A.
hasAcademicFacilities
chosen
Indicates that an entity provides or is equipped with academic facilities such as classrooms, laboratories, libraries, or other educational infrastructure.
-
B.
computingCenter
Indicates that an entity functions as or is associated with a computing center, i.e., a facility or unit where computing resources and services are provided or managed.
-
C.
hasLectureHall
Indicates that an entity possesses, includes, or is associated with a lecture hall as part of its facilities or structure.
-
D.
numberOfLabs
Indicates the quantity or count of laboratories associated with a given entity.
-
E.
hasComputerWorkstations
Indicates that an entity is equipped with or provides access to computer workstations.
- 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.