Triple
T12691470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qutb complex |
E303213
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Saket |
E698912
|
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: Saket | Statement: [Qutb complex, near, Saket]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saket Context triple: [Qutb complex, near, Saket]
-
A.
Saket
chosen
Saket is a prominent residential and commercial neighborhood in South Delhi, India, known for its shopping malls, cinemas, and proximity to major urban hubs.
-
B.
Mankhurd
Mankhurd is a suburban locality in eastern Mumbai known for its residential areas, railway station, and proximity to industrial and coastal zones.
-
C.
Rajgurunagar
Rajgurunagar is a town in Maharashtra, India, historically notable as the birthplace of Indian revolutionary freedom fighter Shivaram Rajguru.
-
D.
Ajodhya Hills
Ajodhya Hills is a scenic hill range in West Bengal, India, known for its forested landscapes, waterfalls, tribal villages, and trekking opportunities.
-
E.
Dunyapur
Dunyapur is a city in the Lodhran District of southern Punjab, Pakistan, known as a local commercial and agricultural center in the region.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961dabb38819087738361f9de8066 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c7a79908190b83a868090990bbe |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 9, 2026, 5:22 p.m.