Triple
T6619986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapti River |
E149648
|
entity |
| Predicate | sourceLocation |
P40
|
FINISHED |
| Object | Multai |
E601131
|
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: Multai | Statement: [Tapti River, sourceLocation, Multai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Multai Context triple: [Tapti River, sourceLocation, Multai]
-
A.
Multai
chosen
Multai is a town in Madhya Pradesh, India, known as a traditional source region of the Tapti River and a local religious and commercial center.
-
B.
Mandulis
Mandulis is a Nubian sun god venerated in the region of Lower Nubia, particularly during the Greco-Roman period.
-
C.
Tahkuna
Tahkuna is a coastal settlement in northern Estonia, located on Hiiumaa Island and known for its proximity to the historic Tahkuna Lighthouse.
-
D.
Molėtai
Molėtai is a small town in northeastern Lithuania known for its surrounding lakes, observatory, and role as a regional tourist and recreational center.
-
E.
Kaikesi
Kaikesi is a figure in the Hindu epic Ramayana, known as the rakshasi queen of Lanka and the mother of Ravana, Kumbhakarna, and Vibhishana.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af5ca97481909f8a7dc47249b4d3 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e4461e748190b4feead6ef16a01c |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:58 p.m.