Triple
T8564654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamil New Year |
E202773
|
entity |
| Predicate | hasGreeting |
P5241
|
FINISHED |
| Object | Iniya Puthandu Nalvazhthukkal |
—
|
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: Iniya Puthandu Nalvazhthukkal | Statement: [Tamil New Year, hasGreeting, Iniya Puthandu Nalvazhthukkal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreeting Context triple: [Tamil New Year, hasGreeting, Iniya Puthandu Nalvazhthukkal]
-
A.
typicalGreeting
Indicates the standard or commonly used way one entity greets another in a given context.
-
B.
hasWordForHello
chosen
Indicates that a language or entity possesses a specific word or expression used to say "hello" or greet.
-
C.
hasGadget
Indicates that an entity possesses, uses, or is equipped with a particular gadget.
-
D.
hasGuestOfHonorFormat
Indicates that an event or occasion is organized in a special format that highlights or centers around a designated guest of honor.
-
E.
hasPresented
Indicates that one entity has formally given, delivered, or shown something (such as information, a work, or an award) to another entity.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d11274819099cc33a21a993a1f |
completed | March 31, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.