Triple
T7121255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divya Prabandham |
E165954
|
entity |
| Predicate | includesPoets |
P32365
|
FINISHED |
| Object | Andal |
E202433
|
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: Andal | Statement: [Divya Prabandham, includesPoets, Andal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andal Context triple: [Divya Prabandham, includesPoets, Andal]
-
A.
Andal
Andal is a town in the Paschim Bardhaman district of West Bengal, India, known as a coal mining and industrial hub in the Raniganj coalfield region.
-
B.
Andal
chosen
Andal is a revered female Tamil Vaishnavite saint and poet, celebrated for her devotional hymns to Vishnu and her central place in the Sri Vaishnavism tradition.
-
C.
Arandis
Arandis is a small mining town in Namibia known primarily for its proximity to the Rossing uranium mine.
-
D.
Andalasia
Andalasia is the whimsical fairy-tale kingdom from Disney’s film "Enchanted," characterized by its classic animated princess world and magical charm.
-
E.
Azania
Azania is a name used by some African liberation movements and activists to refer to a decolonized, non-apartheid South Africa.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7759a048190815689298befa8d7 |
completed | March 27, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a32ba9588190a078723207c4f823 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:44 p.m.