Triple
T19708704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sajibu Nongma Panba |
E473282
|
entity |
| Predicate | occursInMonth |
P1167
|
FINISHED |
| Object |
Sajibu
Sajibu is the first month of the traditional Meitei lunar calendar, marking the beginning of the new year in Manipur.
|
E1391604
|
NE FINISHED |
How this triple was built (4 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: Sajibu | Statement: [Sajibu Nongma Panba, occursInMonth, Sajibu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sajibu Context triple: [Sajibu Nongma Panba, occursInMonth, Sajibu]
-
A.
Takabisha
Takabisha is a record-breaking steel roller coaster in Japan renowned for its extremely steep drop and intense thrill elements.
-
B.
Shobijin
Shobijin are the tiny twin priestesses who serve as Mothra’s mystical spokespeople and guardians in the Godzilla and broader kaiju film universe.
-
C.
Sooretama
Sooretama is a municipality in the Brazilian state of Espírito Santo, known for its proximity to the Sooretama Biological Reserve and its Atlantic Forest conservation areas.
-
D.
Saihat
Saihat is a coastal city in Saudi Arabia’s Eastern Province, known for its fishing heritage and proximity to major oil and industrial centers in the Gulf region.
-
E.
Saib
Saib is a character in Matthew Lewis's Gothic melodrama "The Castle Spectre," contributing to the play's dark, suspenseful atmosphere.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sajibu Triple: [Sajibu Nongma Panba, occursInMonth, Sajibu]
Generated description
Sajibu is the first month of the traditional Meitei lunar calendar, marking the beginning of the new year in Manipur.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sajibu Target entity description: Sajibu is the first month of the traditional Meitei lunar calendar, marking the beginning of the new year in Manipur.
-
A.
Takabisha
Takabisha is a record-breaking steel roller coaster in Japan renowned for its extremely steep drop and intense thrill elements.
-
B.
Shobijin
Shobijin are the tiny twin priestesses who serve as Mothra’s mystical spokespeople and guardians in the Godzilla and broader kaiju film universe.
-
C.
Sooretama
Sooretama is a municipality in the Brazilian state of Espírito Santo, known for its proximity to the Sooretama Biological Reserve and its Atlantic Forest conservation areas.
-
D.
Saihat
Saihat is a coastal city in Saudi Arabia’s Eastern Province, known for its fishing heritage and proximity to major oil and industrial centers in the Gulf region.
-
E.
Saib
Saib is a character in Matthew Lewis's Gothic melodrama "The Castle Spectre," contributing to the play's dark, suspenseful atmosphere.
- F. None of above. chosen
Provenance (5 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642bc754481908bdf5bfad069aec8 |
completed | April 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ab9cbf0c8190a34ceeeb9960677b |
completed | May 15, 2026, 11:26 p.m. |
| NEDg | Description generation | batch_6a07ac51fddc8190840698fb5cee0ea0 |
completed | May 15, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ae6493608190b8bc885ab8a916b2 |
completed | May 15, 2026, 11:38 p.m. |
Created at: April 10, 2026, 1:46 p.m.