Triple
T8614709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vandiyur Mariamman Teppakulam |
E204006
|
entity |
| Predicate | festivalHonors |
P43480
|
FINISHED |
| Object | Mariamman |
E745468
|
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: Mariamman | Statement: [Vandiyur Mariamman Teppakulam, festivalHonors, Mariamman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mariamman Context triple: [Vandiyur Mariamman Teppakulam, festivalHonors, Mariamman]
-
A.
Mariamman
chosen
Mariamman is a South Indian Hindu goddess primarily associated with rain, fertility, and the cure of diseases such as smallpox.
-
B.
Mariam Bai
Mariam Bai was a member of the prominent Jinnah family, historically notable in the context of South Asian politics and the creation of Pakistan.
-
C.
Maryam
Maryam is a revered figure in Islam, honored in the Qur’an as the mother of Prophet Isa (Jesus) and a model of piety and devotion.
-
D.
Ayesha
Ayesha is a central fictional heroine in Bankim Chandra Chattopadhyay’s historical Bengali novel "Durgeshnandini," known for her beauty, courage, and tragic love.
-
E.
Karima
Karima is a town in northern Sudan known as a gateway to the ancient Nubian archaeological area around Gebel Barkal and the Napatan sites.
- 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_69ca832ceab8819096e4a9f546695079 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc47020748819090f658c115c1a7b9 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebbc1d8a08190bbcf7c4cef0fe04d |
completed | April 2, 2026, 6:56 p.m. |
Created at: March 30, 2026, 6:25 p.m.