Triple
T17412956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lodhran |
E423413
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Khanewal |
—
|
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: Khanewal | Statement: [Lodhran, hasNearbyCity, Khanewal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khanewal Context triple: [Lodhran, hasNearbyCity, Khanewal]
-
A.
Khanewal
chosen
Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
-
B.
Chakwal
Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
-
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.
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.
-
E.
Sargodha
Sargodha is a major city in central Pakistan known for its air force base and extensive citrus (particularly kinnow) production.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b0c12b881908b2ddc13678c7a75 |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.