Triple
T2917119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nawabshah |
E78632
|
entity |
| Predicate | languageSpoken |
P151
|
FINISHED |
| Object | Seraiki |
E41867
|
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: Seraiki | Statement: [Nawabshah, languageSpoken, Seraiki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seraiki Context triple: [Nawabshah, languageSpoken, Seraiki]
-
A.
Seraiki
chosen
Seraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
-
B.
Gorani
Gorani is a Northwestern Iranian language variety traditionally spoken by Kurdish communities in parts of Iran and Iraq, notable for its rich literary and religious heritage.
-
C.
Siwi
Siwi is a Berber language spoken primarily in Egypt’s Siwa Oasis, known for its unique features and relative isolation from other Berber varieties.
-
D.
Kurmanji
Kurmanji is the most widely spoken dialect of the Kurdish language, used primarily by Kurds across Turkey, Syria, Iraq, Iran, and the diaspora.
-
E.
Turoyo
Turoyo is a modern Neo-Aramaic language traditionally spoken by Syriac Orthodox Christian communities from the Tur Abdin region of southeastern Turkey and neighboring areas.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a2bdd88190aa01c26a27f9afbd |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0562847488190a0d6b7de99796cd9 |
completed | March 10, 2026, 5:34 p.m. |
Created at: March 8, 2026, 2:53 p.m.