Triple
T12828698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyari Town |
E306728
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Lyari River |
—
|
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: Lyari River | Statement: [Lyari Town, hasRiver, Lyari River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyari River Context triple: [Lyari Town, hasRiver, Lyari River]
-
A.
Lyari River
chosen
The Lyari River is a small, heavily polluted seasonal river flowing through Karachi, Pakistan, that has become a major urban drainage channel.
-
B.
Kaidu River
The Kaidu River is a significant river in Xinjiang, China, that flows through the Bayinbulak Grassland and feeds Bosten Lake, supporting agriculture and settlements such as the city of Korla.
-
C.
Karura River
Karura River is a watercourse flowing through Nairobi’s Karura Forest, contributing to the forest’s rich biodiversity and scenic natural environment.
-
D.
Bohtan River
The Bohtan River is a significant watercourse in southeastern Turkey that flows through rugged, mountainous terrain before joining the Tigris River.
-
E.
Bara River
The Bara River is a tributary of the Kabul River flowing through the Khyber Pakhtunkhwa region of Pakistan, passing near the city of Peshawar.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96faf9ae481908265e198f917d1e6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:34 p.m.