Triple
T13403932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaheed Benazirabad District |
E319900
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Sakrand
Sakrand is a town in Pakistan’s Sindh province that serves as a local commercial and agricultural center within the Shaheed Benazirabad District.
|
E1038114
|
NE FINISHED |
How this triple was built (4 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: Sakrand | Statement: [Shaheed Benazirabad District, hasSettlement, Sakrand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sakrand Context triple: [Shaheed Benazirabad District, hasSettlement, Sakrand]
-
A.
Saratak
Saratak is a rural village located in Armenia's Shirak Province.
-
B.
Sakia
Sakia is a prominent cultural center and arts venue in Cairo, Egypt, known for hosting concerts, exhibitions, and a wide range of cultural events.
-
C.
Saklan
Saklan is a Native American group historically associated with the Bay Miwok peoples of the San Francisco Bay Area in California.
-
D.
Sancar
Sancar is the surname of Aziz Sancar, a Turkish-American biochemist and molecular biologist renowned for his Nobel Prize–winning work on DNA repair.
-
E.
Sangan
Sangan is a town located in Pakistan’s Balochistan province within the Sibi District.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Sakrand Triple: [Shaheed Benazirabad District, hasSettlement, Sakrand]
Generated description
Sakrand is a town in Pakistan’s Sindh province that serves as a local commercial and agricultural center within the Shaheed Benazirabad District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sakrand Target entity description: Sakrand is a town in Pakistan’s Sindh province that serves as a local commercial and agricultural center within the Shaheed Benazirabad District.
-
A.
Saratak
Saratak is a rural village located in Armenia's Shirak Province.
-
B.
Sakia
Sakia is a prominent cultural center and arts venue in Cairo, Egypt, known for hosting concerts, exhibitions, and a wide range of cultural events.
-
C.
Saklan
Saklan is a Native American group historically associated with the Bay Miwok peoples of the San Francisco Bay Area in California.
-
D.
Sancar
Sancar is the surname of Aziz Sancar, a Turkish-American biochemist and molecular biologist renowned for his Nobel Prize–winning work on DNA repair.
-
E.
Sangan
Sangan is a town located in Pakistan’s Balochistan province within the Sibi District.
- F. None of above. chosen
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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4ae47081909b68a9aaa62fd4c7 |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7307904608190ad647f741c08dc42 |
completed | May 3, 2026, 11:24 a.m. |
| NEDg | Description generation | batch_69f731d83ca081909ff0762c01280993 |
completed | May 3, 2026, 11:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7324625288190bed99890ba021e46 |
completed | May 3, 2026, 11:32 a.m. |
Created at: April 9, 2026, 9:34 p.m.