Triple
T11507071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Hunza |
E272811
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Sikandarabad
Sikandarabad is a settlement in the Lower Hunza region of northern Pakistan, situated in the mountainous Hunza Valley of Gilgit-Baltistan.
|
E931820
|
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: Sikandarabad | Statement: [Lower Hunza, hasSettlement, Sikandarabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sikandarabad Context triple: [Lower Hunza, hasSettlement, Sikandarabad]
-
A.
Nasirabad
Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
-
B.
Nasirabad
Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
-
C.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
-
D.
Sultanabad
Sultanabad is the former name of the Iranian city now known as Arak, an important industrial and historical center in central Iran.
-
E.
Shamshabad
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
- 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: Sikandarabad Triple: [Lower Hunza, hasSettlement, Sikandarabad]
Generated description
Sikandarabad is a settlement in the Lower Hunza region of northern Pakistan, situated in the mountainous Hunza Valley of Gilgit-Baltistan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sikandarabad Target entity description: Sikandarabad is a settlement in the Lower Hunza region of northern Pakistan, situated in the mountainous Hunza Valley of Gilgit-Baltistan.
-
A.
Nasirabad
Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
-
B.
Nasirabad
chosen
Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
-
C.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
-
D.
Sultanabad
Sultanabad is the former name of the Iranian city now known as Arak, an important industrial and historical center in central Iran.
-
E.
Shamshabad
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
- F. None of above.
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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d86db43a648190be859bec2fe9f43b |
completed | April 10, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e71362e59481909675a1a784dcf7fd |
completed | April 21, 2026, 6:04 a.m. |
| NEDg | Description generation | batch_69e720f4015c81909ba7973c3e781985 |
completed | April 21, 2026, 7:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e75a7a04c88190bb8f3dd3f3e435ef |
completed | April 21, 2026, 11:07 a.m. |
Created at: April 8, 2026, 9:36 p.m.