Triple
T21773016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akshaya Tritiya |
E537482
|
entity |
| Predicate | occursIn |
P40
|
FINISHED |
| Object | April |
—
|
NE NERFINISHED |
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: April | Statement: [Akshaya Tritiya, occursIn, April]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: April Context triple: [Akshaya Tritiya, occursIn, April]
-
A.
April
chosen
April is a spring month in the Gregorian calendar often associated with mild weather and the blooming of many flowers.
-
B.
Aprile
Aprile is a 1998 Italian semi-autobiographical comedy-drama film directed by and starring Nanni Moretti, blending personal diary-style reflections with political commentary.
-
C.
Aprile
Aprile is a fictional character in Robert Browning’s dramatic poem "Paracelsus," representing the idealistic, art-driven counterpart to Paracelsus’s pursuit of knowledge and power.
-
D.
May
May is a character associated with the Cosey Hotel and Resort, likely playing a significant role in its story or setting.
-
E.
May
May is a common English surname borne by numerous individuals, including former UK Prime Minister Theresa May.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031af6a488190a2dcebed43d199d4 |
completed | April 28, 2026, 4:03 a.m. |
Created at: April 16, 2026, 6:51 p.m.