Triple
T20630547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramayana (Tamil retelling) |
E506941
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Hanuman |
—
|
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: Hanuman | Statement: [Ramayana (Tamil retelling), featuresCharacter, Hanuman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanuman Context triple: [Ramayana (Tamil retelling), featuresCharacter, Hanuman]
-
A.
Hanuman
chosen
Hanuman is a revered Hindu deity known for his immense strength, unwavering devotion to Lord Rama, and central role in the epic Ramayana.
-
B.
Hanuman Pol
Hanuman Pol is one of the main historic entrance gates of Rajasthan’s Kumbhalgarh Fort, serving as a fortified access point and defensive structure.
-
C.
Anjaneya
Anjaneya is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and selfless service.
-
D.
Rama
Rama is a river in Bosnia and Herzegovina that flows through mountainous terrain before joining the Neretva River.
-
E.
Rama
Rama is a well-known margarine and spread brand widely used for cooking and baking in various international markets.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad09c71881909698d3c2576cc181 |
completed | April 20, 2026, 10:47 p.m. |
Created at: April 16, 2026, 11:42 a.m.