Triple
T3408979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charminar |
E71843
|
entity |
| Predicate | nearbyFeature |
P2064
|
FINISHED |
| Object | Laad Bazaar |
E349848
|
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: Laad Bazaar | Statement: [Charminar, nearbyFeature, Laad Bazaar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laad Bazaar Context triple: [Charminar, nearbyFeature, Laad Bazaar]
-
A.
Laad Bazaar
chosen
Laad Bazaar is a historic and bustling market in Hyderabad, India, famed for its traditional lacquer bangles, bridal wear, and old-city charm near the Charminar.
-
B.
Lakkar Bazaar
Lakkar Bazaar is a popular wooden handicrafts market and shopping area in Shimla, known for its traditional souvenirs and vibrant local atmosphere.
-
C.
Vakil Bazaar
Vakil Bazaar is a historic covered market in Shiraz, Iran, renowned for its traditional architecture and vibrant trade in local goods and handicrafts.
-
D.
Raja Bazaar
Raja Bazaar is a major, densely packed commercial and shopping area in Rawalpindi, Pakistan, known for its traditional markets, wholesale trade, and bustling street life.
-
E.
Anarkali Bazaar
Anarkali Bazaar is one of the oldest and busiest traditional markets in Lahore, Pakistan, known for its dense network of shops selling clothing, jewelry, handicrafts, and street food.
- 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9056acc8190a9c50ec374851ac8 |
completed | March 8, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bdd99248190823875cae2531609 |
completed | March 12, 2026, 11:27 p.m. |
Created at: March 8, 2026, 3:15 p.m.