Triple
T7842522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellow Line (Delhi Metro) |
E181839
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Arjan Garh
Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
|
E705587
|
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: Arjan Garh | Statement: [Yellow Line (Delhi Metro), hasStation, Arjan Garh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arjan Garh Context triple: [Yellow Line (Delhi Metro), hasStation, Arjan Garh]
-
A.
Naraingarh
Naraingarh is a town in the northern Indian state of Haryana, known for its agricultural surroundings and role as a local commercial center.
-
B.
Kapadvanj
Kapadvanj is a historic town in the Kheda district of Gujarat, India, known for its traditional markets and regional cultural heritage.
-
C.
Khajauli
Khajauli is a town located in the Madhubani district of the Indian state of Bihar.
-
D.
Bhit Shah
Bhit Shah is a town in Sindh, Pakistan, renowned as a spiritual and cultural center built around the shrine of the revered Sufi poet Shah Abdul Latif Bhittai.
-
E.
Kheragarh
Kheragarh is a town in the culturally significant Braj region of northern India, known for its historical and religious associations with the broader Mathura–Agra area.
- 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: Arjan Garh Triple: [Yellow Line (Delhi Metro), hasStation, Arjan Garh]
Generated description
Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arjan Garh Target entity description: Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
-
A.
Naraingarh
Naraingarh is a town in the northern Indian state of Haryana, known for its agricultural surroundings and role as a local commercial center.
-
B.
Kapadvanj
Kapadvanj is a historic town in the Kheda district of Gujarat, India, known for its traditional markets and regional cultural heritage.
-
C.
Khajauli
Khajauli is a town located in the Madhubani district of the Indian state of Bihar.
-
D.
Bhit Shah
Bhit Shah is a town in Sindh, Pakistan, renowned as a spiritual and cultural center built around the shrine of the revered Sufi poet Shah Abdul Latif Bhittai.
-
E.
Kheragarh
Kheragarh is a town in the culturally significant Braj region of northern India, known for its historical and religious associations with the broader Mathura–Agra area.
- 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_69cb163b32688190b463a9cd8fa3c690 |
completed | March 31, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdf0dee3881908f817427143cf774 |
completed | March 31, 2026, 2:49 p.m. |
| NEDg | Description generation | batch_69cc46bca04481908852425c214a4e34 |
completed | March 31, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc49129e188190aaebd6a1188788d9 |
completed | March 31, 2026, 10:22 p.m. |
Created at: March 30, 2026, 4:48 p.m.