Triple
T17952795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revanta |
E448872
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Tapati |
—
|
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: Tapati | Statement: [Revanta, sibling, Tapati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tapati Context triple: [Revanta, sibling, Tapati]
-
A.
Tapati
chosen
Tapati is a goddess in Hindu mythology, known as a daughter of the sun god Surya and associated with heat and devotion.
-
B.
Dharapani
Dharapani is a village in Nepal’s Annapurna region that serves as a key trekking junction and gateway between the Manaslu and Annapurna Circuit routes.
-
C.
Taramani
Taramani is a neighborhood in Chennai, India, known for its educational institutions, research centers, and growing IT and technology hubs.
-
D.
Baghmara
Baghmara is a town in the South Garo Hills district of Meghalaya, India, known as a gateway to nearby forests, caves, and wildlife areas.
-
E.
Barapani
Barapani is a scenic lakeside area in Meghalaya, India, known for the Umiam Lake reservoir and its proximity to Shillong.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afad61f481908b34cd24de88983c |
completed | April 19, 2026, 10:34 a.m. |
Created at: April 10, 2026, 10:21 a.m.