Triple
T27262602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamil Nadu Engineering Admissions |
E687806
|
entity |
| Predicate | counselingMode |
P125712
|
FINISHED |
| Object | centralized |
—
|
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: centralized | Statement: [Tamil Nadu Engineering Admissions, counselingMode, centralized]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: counselingMode Context triple: [Tamil Nadu Engineering Admissions, counselingMode, centralized]
-
A.
featuresCounselFrom
Indicates that one entity includes or presents counsel, advice, or legal representation provided by another entity.
-
B.
communicationMode
Indicates the method or channel through which communication between entities is carried out.
-
C.
consultationSetting
chosen
Indicates the context or environment in which a consultation or advisory interaction takes place.
-
D.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
E.
promptType
Indicates the specific category or style of a prompt that characterizes how an instruction or request is framed or intended to be interpreted.
- 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_69ef3557abc481908bf3c146f0f3356a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f626f07218819080448c001f01ba45 |
completed | May 2, 2026, 4:31 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 10:53 a.m.