Triple
T941945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganesha |
E20323
|
entity |
| Predicate | hasAspect |
P642
|
FINISHED |
| Object | Lambodara |
E122748
|
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: Lambodara | Statement: [Ganesha, hasAspect, Lambodara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lambodara Context triple: [Ganesha, hasAspect, Lambodara]
-
A.
Vakratunda
chosen
Vakratunda is a revered aspect of the Hindu deity Ganesha, depicted with a curved trunk and associated with the removal of obstacles and the subduing of evil forces.
-
B.
Ananta
Ananta is the cosmic serpent in Hindu mythology who serves as the endless, thousand-headed couch of the god Vishnu and symbolizes infinity and timelessness.
-
C.
Gudakesha
Gudakesha is an epithet of the warrior prince Arjuna from the Indian epic Mahabharata, highlighting his mastery over sleep and unwavering focus.
-
D.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
E.
Kishkindha
Kishkindha is the mythical monkey kingdom ruled by Sugriva in the Indian epic Ramayana, where Rama forms an alliance with the vanara army to search for Sita.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a1a4888190997adf56eb761431 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac599117d48190b329ec50b9a632fc |
completed | March 7, 2026, 5 p.m. |
Created at: March 1, 2026, 7:40 p.m.