Triple
T11132941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murree Road |
E263332
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Faizabad area |
E64151
|
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: Faizabad area | Statement: [Murree Road, passesThrough, Faizabad area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faizabad area Context triple: [Murree Road, passesThrough, Faizabad area]
-
A.
Faizabad
chosen
Faizabad is a historic city in the Indian state of Uttar Pradesh that once served as the capital of the former princely state of Oudh (Awadh).
-
B.
Faizabad division
Faizabad division is an administrative division in the Indian state of Uttar Pradesh that encompasses several districts and parliamentary constituencies, including Amethi.
-
C.
Shahabad region
The Shahabad region is a historical area in the Indian state of Bihar, known for its former feudal estates and role in regional politics and agrarian society.
-
D.
Nizamuddin area
Nizamuddin area is a historic neighborhood in Delhi, India, known for its Sufi shrines, Mughal-era monuments, and vibrant cultural and religious life.
-
E.
North Nazimabad Town
North Nazimabad Town is a prominent residential and commercial neighborhood in Karachi, Pakistan, known for its planned layout and middle-class population.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8347a248190837e8c26f25f553a |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e441f00d7c8190a8fe8e0c1169e6b0 |
completed | April 19, 2026, 2:46 a.m. |
Created at: April 8, 2026, 9:28 p.m.