Triple
T2525972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oude |
E56035
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Faizabad |
E64151
|
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: Faizabad | Statement: [Oude, majorCity, Faizabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faizabad Context triple: [Oude, majorCity, Faizabad]
-
A.
Faizabad
chosen
Faizabad is a historic city in the Indian state of Uttar Pradesh that once served as the capital of the former princely state of Oudh (Awadh).
-
B.
Khuldabad
Khuldabad is a historic town in Maharashtra, India, renowned as the burial site of the Mughal emperor Aurangzeb and several prominent Sufi saints.
-
C.
Moradabad
Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
-
D.
Wazirabad
Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
-
E.
Hazratganj
Hazratganj is a historic and bustling commercial and cultural hub in Lucknow, known for its colonial-era architecture, shopping arcades, and vibrant street life.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2544b4481908e105294cebdbb1f |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af9068798c8190958c5522276906fe |
completed | March 10, 2026, 3:30 a.m. |
Created at: March 6, 2026, 9:46 p.m.