Triple
T17762338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gujranwala Campus |
E443408
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Gujranwala |
—
|
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: Gujranwala | Statement: [Gujranwala Campus, locatedIn, Gujranwala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gujranwala Context triple: [Gujranwala Campus, locatedIn, Gujranwala]
-
A.
Gujranwala
chosen
Gujranwala is a major industrial city in Pakistan’s Punjab province, known for its manufacturing base and historical significance in the region.
-
B.
Jhang
Jhang is a historic city in the Punjab province of Pakistan, known for its cultural heritage and as the birthplace of several notable figures.
-
C.
Mandi Bahauddin
Mandi Bahauddin is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub in the region.
-
D.
Khanewal
Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
-
E.
Rahim Yar Khan
Rahim Yar Khan is a major city in southern Punjab, Pakistan, known as an important commercial and agricultural center in the Seraiki-speaking region.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485f887ac81908c896a50175692b9 |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 10:11 a.m.