Triple
T12882073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qaumi Tarana |
E308120
|
entity |
| Predicate | firstLineInEnglishTransliteration |
P104676
|
FINISHED |
| Object | Pāk sarzamīn shād bād |
—
|
LITERAL 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: Pāk sarzamīn shād bād | Statement: [Qaumi Tarana, firstLineInEnglishTransliteration, Pāk sarzamīn shād bād]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLineInEnglishTransliteration Context triple: [Qaumi Tarana, firstLineInEnglishTransliteration, Pāk sarzamīn shād bād]
-
A.
firstLineTranslation
Indicates that one text is a translation of the first line of another text.
-
B.
openingVerseTransliteration
chosen
Indicates the transliterated form of the opening verse of a text, showing how it is pronounced using a target script or phonetic system.
-
C.
firstLineAfrikaans
Indicates that the specified text is the first line of a piece of content when written in Afrikaans.
-
D.
firstLetter
Indicates that one entity is the initial character or starting letter of another entity (typically a string or word).
-
E.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
- F. None of above.
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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.