Triple
T15956457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kot Diji Fort |
E386946
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Khairpur city |
E160202
|
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: Khairpur city | Statement: [Kot Diji Fort, near, Khairpur city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khairpur city Context triple: [Kot Diji Fort, near, Khairpur city]
-
A.
Khairpur
chosen
Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
-
B.
Shikarpur
Shikarpur is a historic city in the Sindh province of Pakistan, known for its old trading heritage and distinctive cultural and architectural traditions.
-
C.
Bahawalnagar
Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
-
D.
Mandi Bahauddin
Mandi Bahauddin is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub in the region.
-
E.
Multan
Multan is a historic city in southern Punjab, Pakistan, renowned as a major cultural, commercial, and Sufi spiritual center with a legacy spanning over two millennia.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fb29848190a55cabb49cb19575 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff794c8508190a444af7ce968c5da |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 4:53 a.m.