Triple
T7844799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jodhpur district |
E181896
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Shergarh
Shergarh is a town in the Jodhpur district of Rajasthan, India, known for its rural setting and local administrative significance.
|
E699858
|
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: Shergarh | Statement: [Jodhpur district, containsTown, Shergarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shergarh Context triple: [Jodhpur district, containsTown, Shergarh]
-
A.
Shergarh
Shergarh is the inner fortification within Pakistan’s historic Ranikot Fort, noted for its strategic defensive position and architectural significance.
-
B.
Rakhsh
Rakhsh is the legendary, powerful warhorse of the Persian hero Rostam in the epic Shahnameh.
-
C.
Lashkar
Lashkar is a historic suburb of Gwalior in Madhya Pradesh, India, known as a former princely capital and an important administrative and commercial center.
-
D.
Landi Kotal
Landi Kotal is a town in Pakistan’s Khyber District, historically significant as a key trading and military post near the Khyber Pass on the route to Afghanistan.
-
E.
Chiniot
Chiniot is a historic city in Pakistan’s Punjab province, renowned for its intricate woodwork, furniture craftsmanship, and architectural heritage along the Chenab River.
- 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: Shergarh Triple: [Jodhpur district, containsTown, Shergarh]
Generated description
Shergarh is a town in the Jodhpur district of Rajasthan, India, known for its rural setting and local administrative significance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shergarh Target entity description: Shergarh is a town in the Jodhpur district of Rajasthan, India, known for its rural setting and local administrative significance.
-
A.
Shergarh
Shergarh is the inner fortification within Pakistan’s historic Ranikot Fort, noted for its strategic defensive position and architectural significance.
-
B.
Rakhsh
Rakhsh is the legendary, powerful warhorse of the Persian hero Rostam in the epic Shahnameh.
-
C.
Lashkar
Lashkar is a historic suburb of Gwalior in Madhya Pradesh, India, known as a former princely capital and an important administrative and commercial center.
-
D.
Landi Kotal
Landi Kotal is a town in Pakistan’s Khyber District, historically significant as a key trading and military post near the Khyber Pass on the route to Afghanistan.
-
E.
Chiniot
Chiniot is a historic city in Pakistan’s Punjab province, renowned for its intricate woodwork, furniture craftsmanship, and architectural heritage along the Chenab River.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163d92fc8190a4efcb08d6b3d404 |
completed | March 31, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5ae9758c819091e270343ed289aa |
completed | March 31, 2026, 5:26 a.m. |
| NEDg | Description generation | batch_69cb762eab0881909c5035b3086dfdd9 |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbb801cc0c8190864d28e199eb5e67 |
completed | March 31, 2026, 12:03 p.m. |
Created at: March 30, 2026, 4:48 p.m.