Triple
T29265185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ستارہ امتیاز |
E741959
|
entity |
| Predicate | type |
P0
|
FINISHED |
| Object |
تمغہ
تمغہ ایک اعزازی تمغہ یا میڈل ہوتا ہے جو کسی فرد کی نمایاں خدمات یا کارناموں کے اعتراف میں دیا جاتا ہے۔
|
E1859598
|
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: تمغہ | Statement: [ستارہ امتیاز, type, تمغہ]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: تمغہ Triple: [ستارہ امتیاز, type, تمغہ]
Generated description
تمغہ ایک اعزازی تمغہ یا میڈل ہوتا ہے جو کسی فرد کی نمایاں خدمات یا کارناموں کے اعتراف میں دیا جاتا ہے۔
Provenance (5 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_69f0912065c08190bddd23e20e8ef18e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f664de3fec81909fd482a0d6eee6c6 |
completed | May 2, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25893271d48190b1b65ac878ca0508 |
completed | June 7, 2026, 3:07 p.m. |
| NEDg | Description generation | batch_6a258dab84b081908f66170fc8e3151b |
completed | June 7, 2026, 3:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a25919df80881909c817cf6b2c3ef56 |
completed | June 7, 2026, 3:43 p.m. |
Created at: April 28, 2026, 12:44 p.m.