Triple
T30486741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government Engineering College Thrissur |
E775739
|
entity |
| Predicate | hasTechnicalClubs |
P190355
|
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: [Government Engineering College Thrissur, hasTechnicalClubs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTechnicalClubs Context triple: [Government Engineering College Thrissur, hasTechnicalClubs, yes]
-
A.
hasTechnicalSociety
Indicates that an entity is associated with, or possesses membership in, a technical or engineering-focused society or organization.
-
B.
hasSportsClubs
Indicates that an entity possesses, hosts, or is associated with one or more sports clubs.
-
C.
hasTechnicalCommittees
Indicates that an entity maintains or is associated with one or more technical committees.
-
D.
hasTechnicalCollege
Indicates that an entity possesses, includes, or is associated with a technical college as part of its structure or offerings.
-
E.
hasClub
Indicates that an entity is associated with or belongs to a particular club.
- F. None of above. chosen
Provenance (4 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_69f22497f91c8190afa7165bc900accd |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc4b5f22c8190b8b256adbdc2570c |
completed | May 7, 2026, 4:58 p.m. |
Created at: April 29, 2026, 8:13 p.m.