Triple
T1656138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loralai District |
E35802
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Loralai |
E35802
|
NE FINISHED |
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: Loralai | Statement: [Loralai District, hasCapital, Loralai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loralai Context triple: [Loralai District, hasCapital, Loralai]
-
A.
Loralai
chosen
Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
-
B.
Laleia
Laleia is a town in northern Timor-Leste known as the birthplace of independence leader and former president Xanana Gusmão.
-
C.
Zeilin
Zeilin is a surname most notably associated with Jacob Zeilin, the first United States Marine Corps officer to be promoted to the rank of brigadier general.
-
D.
Corrsin
Corrsin is a surname most notably associated with Stanley Corrsin, an influential American fluid dynamicist known for his work on turbulence.
-
E.
Kirsha
Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb4535180819088e3bdaa591dcdbd |
completed | March 7, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad798680088190a24dd968aab1baf0 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:29 p.m.