Triple
T3655179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu’l-Fazl ibn Mubarak |
E77511
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Agra |
E16921
|
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: Agra | Statement: [Abu’l-Fazl ibn Mubarak, birthPlace, Agra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agra Context triple: [Abu’l-Fazl ibn Mubarak, birthPlace, Agra]
-
A.
Agra
chosen
Agra is a historic city in northern India renowned for its Mughal-era architecture, most notably the Taj Mahal and Agra Fort.
-
B.
AGRA
AGRA is an African-based organization focused on transforming smallholder agriculture to improve food security and incomes across the continent.
-
C.
Ayodhya
Ayodhya is an ancient city in India revered in Hinduism as the birthplace of Lord Rama and a major pilgrimage site.
-
D.
Allahabad
Allahabad, officially known as Prayagraj, is a major city in the Indian state of Uttar Pradesh, historically significant as a political and cultural center and as a prominent site of the Kumbh Mela at the confluence of the Ganges, Yamuna, and mythical Saraswati rivers.
-
E.
Aligarh
Aligarh is a prominent city in northern India known for its lock industry and as the home of Aligarh Muslim University.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3baf57c8190b72b5d1b910d9db6 |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4faf8650481908eeb6333c5ba84e6 |
completed | March 14, 2026, 6:06 a.m. |
Created at: March 8, 2026, 3:24 p.m.