Triple
T17412954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lodhran |
E423413
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Multan |
—
|
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: Multan | Statement: [Lodhran, hasNearbyCity, Multan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Multan Context triple: [Lodhran, hasNearbyCity, Multan]
-
A.
Multan
chosen
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.
-
B.
Faisalabad
Faisalabad is a major industrial city in Pakistan’s Punjab province, known especially for its large textile industry and role as a commercial hub.
-
C.
Sukkur
Sukkur is a major city in Pakistan known for its strategic location on the Indus River and its role as an important commercial and cultural center in northern Sindh.
-
D.
Bahawalnagar
Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
-
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_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.