Triple
T8574992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mir Taqi Mir |
E203025
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Lucknow |
E22159
|
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: Lucknow | Statement: [Mir Taqi Mir, deathPlace, Lucknow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucknow Context triple: [Mir Taqi Mir, deathPlace, Lucknow]
-
A.
Lucknow
chosen
Lucknow is the capital city of the Indian state of Uttar Pradesh, renowned for its rich cultural heritage, refined Urdu literature, Awadhi cuisine, and elegant Mughal and colonial-era architecture.
-
B.
Lucknow
Lucknow is a small rural community in Bruce County, Ontario, Canada, known for its agricultural character and local festivals.
-
C.
Kanpur
Kanpur is a major industrial city in the northern Indian state of Uttar Pradesh, historically significant as a key site of conflict during the Indian Rebellion of 1857.
-
D.
Kanpur Central
Kanpur Central is one of the busiest and largest railway stations in North India, serving as a major junction and transit hub in the city of Kanpur, Uttar Pradesh.
-
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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea947f188190af469babaa73ddf6 |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce8995d1d081909f6a27220c2c267e |
completed | April 2, 2026, 3:21 p.m. |
Created at: March 30, 2026, 6:21 p.m.