Triple
T7787169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ranchi University |
E187274
|
entity |
| Predicate | hasConstituentUnit |
P71417
|
FINISHED |
| Object | constituent colleges |
—
|
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: constituent colleges | Statement: [Ranchi University, hasConstituentUnit, constituent colleges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConstituentUnit Context triple: [Ranchi University, hasConstituentUnit, constituent colleges]
-
A.
hasSubunits
chosen
Indicates that an entity is composed of or organized into smaller constituent units that are part of its structure.
-
B.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
C.
hasSeparateUnit
Indicates that one entity exists or is treated as an independent, distinct unit from another entity.
-
D.
hasBasedUnit
Indicates that something is defined or measured in terms of a specified base unit.
-
E.
constitutedBy
Indicates that something is made up of, composed from, or formed by the specified parts or elements.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 4:24 p.m.