Triple
T9032009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuki |
E216393
|
entity |
| Predicate | festival |
P3113
|
FINISHED |
| Object | Mim Kut |
E635197
|
NE 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: Mim Kut | Statement: [Kuki, festival, Mim Kut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mim Kut Context triple: [Kuki, festival, Mim Kut]
-
A.
Mim Kut
chosen
Mim Kut is a traditional Mizo harvest festival marked by offerings to ancestors, communal feasting, and cultural celebrations.
-
B.
Mirik
Mirik is a small hill town and popular tourist destination in the Darjeeling district of West Bengal, India, known for its scenic lake, tea gardens, and pleasant climate.
-
C.
Kutama
Kutama is a rural village in the Zvimba District of northern Zimbabwe, known primarily as the birthplace of former president Robert Mugabe.
-
D.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
-
E.
Muyil
Muyil is an ancient Maya archaeological site in Mexico’s Yucatán Peninsula, known for its well-preserved temples and proximity to the Sian Ka'an Biosphere Reserve.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6a9f2c7481909b4a272183f20585 |
completed | April 1, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdbc9c6e08190aa71d84316afc6d5 |
completed | April 3, 2026, 3:24 p.m. |
Created at: March 30, 2026, 7:08 p.m.