Triple
T18692743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dakhni |
E457039
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Standard Urdu |
E6054
|
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: Standard Urdu | Statement: [Dakhni, relatedTo, Standard Urdu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Standard Urdu Context triple: [Dakhni, relatedTo, Standard Urdu]
-
A.
Urdu language
chosen
Urdu is a major South Asian language, written in a Perso-Arabic script and widely used in Pakistan and parts of India in literature, media, and everyday communication.
-
B.
Abbottabadi Hindko
Abbottabadi Hindko is a regional variety of the Hindko language spoken primarily in and around the city of Abbottabad in northern Pakistan.
-
C.
Saraiki
Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
-
D.
Karachi Urdu
Karachi Urdu is an urban dialect of Urdu shaped by the speech of Muhajir communities in Karachi, marked by distinctive pronunciation, vocabulary, and influences from local languages.
-
E.
Sindhi Khudabadi
Sindhi Khudabadi is a historical script used primarily by Sindhi-speaking merchant communities for writing the Sindhi language, especially in commercial and administrative contexts.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e4756881909335e1e7b3c23e28 |
completed | April 19, 2026, 11:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0523605508819089bce4771fe9f9f6 |
completed | May 14, 2026, 1:20 a.m. |
Created at: April 10, 2026, 11:49 a.m.