Triple
T14430906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ladyfinger Peak |
E357824
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Karimabad |
E271539
|
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: Karimabad | Statement: [Ladyfinger Peak, near, Karimabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karimabad Context triple: [Ladyfinger Peak, near, Karimabad]
-
A.
Karimabad
chosen
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.
-
B.
Karimabad
Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
-
C.
Umarkot
Umarkot is a historic town in the Sindh province of Pakistan, traditionally known as the birthplace of the Mughal emperor Akbar.
-
D.
Khoshbagh
Khoshbagh is a historic garden-cemetery complex in Murshidabad, West Bengal, known as the burial place of several Nawabs of Bengal.
-
E.
Jauharabad
Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914570f08190b1c7c1c57a0cb476 |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aa705e08190bff1ab4125bd773f |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:18 a.m.