Triple
T7641423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Pakistan |
E173018
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Umerkot |
E79535
|
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: Umerkot | Statement: [Southern Pakistan, hasMajorCity, Umerkot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umerkot Context triple: [Southern Pakistan, hasMajorCity, Umerkot]
-
A.
Umarkot
chosen
Umarkot is a historic town in the Sindh province of Pakistan, traditionally known as the birthplace of the Mughal emperor Akbar.
-
B.
Khuzdar
Khuzdar is a major city in central Balochistan that serves as an important regional commercial and administrative center in southwestern Pakistan.
-
C.
Amarkot
Amarkot is an alternative name for Umarkot, a historic town and district in the Sindh province of Pakistan known for its cultural and Mughal-era significance.
-
D.
Karimabad
Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
-
E.
Karimabad
Karimabad is a picturesque town in northern Pakistan’s Hunza region, known for its stunning mountain scenery, historic forts, and role as a popular base for trekkers and tourists.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facefbe08190882bd76cf3cd605e |
completed | March 27, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89ac251308190a09814cc469d80fd |
completed | March 29, 2026, 3:21 a.m. |
Created at: March 27, 2026, 3:57 p.m.