Triple
T2014386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrinalini Devi |
E43760
|
entity |
| Predicate | spouseNotableWork |
P19181
|
FINISHED |
| Object | Gora |
E49286
|
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: Gora | Statement: [Mrinalini Devi, spouseNotableWork, Gora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gora Context triple: [Mrinalini Devi, spouseNotableWork, Gora]
-
A.
Gora
chosen
Gora is a major Bengali novel by Rabindranath Tagore that explores themes of identity, nationalism, and religious and social reform in colonial India.
-
B.
Dinara mountain
Dinara mountain is a prominent peak on the border of Croatia and Bosnia and Herzegovina, known as the highest mountain in Croatia and a key part of the rugged Dinaric mountain system.
-
C.
Czarna Góra
Czarna Góra is a village in southern Poland, known as a mountain resort area in the Tatra region.
-
D.
Lata Mountain
Lata Mountain is the tallest peak on the island of Taʻū in American Samoa, known for its lush tropical rainforest and dramatic volcanic terrain.
-
E.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b610a88190bc10fd7dda19da08 |
completed | March 7, 2026, 5:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0aeca6388190befe0630d44de109 |
completed | March 8, 2026, 11:49 p.m. |
Created at: March 4, 2026, 7:37 p.m.