Triple
T21202608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheikhupura District |
E522493
|
entity |
| Predicate | railConnection |
P848
|
FINISHED |
| Object | Faisalabad |
—
|
NE NERFINISHED |
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: Faisalabad | Statement: [Sheikhupura District, railConnection, Faisalabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faisalabad Context triple: [Sheikhupura District, railConnection, Faisalabad]
-
A.
Faisalabad
chosen
Faisalabad is a major industrial city in Pakistan’s Punjab province, known especially for its large textile industry and role as a commercial hub.
-
B.
مظفرآباد
مظفرآباد آزاد جموں و کشمیر کا دارالحکومت اور دریائے نیلم و جہلم کے سنگم پر واقع ایک اہم تاریخی و جغرافیائی شہر ہے۔
-
C.
Bahawalpur
Bahawalpur is a historic city in southern Punjab, Pakistan, known for its former princely state status, grand palaces, and proximity to the Cholistan Desert.
-
D.
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.
-
E.
Bahawalnagar
Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73432a2b88190a89e636626d40c9b |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 3:19 p.m.