Triple
T686031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haryana |
E13284
|
entity |
| Predicate | majorIndustryHub |
P11547
|
FINISHED |
| Object | Faridabad |
E131142
|
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: Faridabad | Statement: [Haryana, majorIndustryHub, Faridabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faridabad Context triple: [Haryana, majorIndustryHub, Faridabad]
-
A.
Faridabad
chosen
Faridabad is a major industrial city in northern India known for its manufacturing sector and its location within the National Capital Region near New Delhi.
-
B.
Ghaziabad
Ghaziabad is a major industrial and residential city in the Indian state of Uttar Pradesh, forming part of the National Capital Region near Delhi.
-
C.
Meerut
Meerut is a historic city in the Indian state of Uttar Pradesh, known as the place where the Indian Rebellion of 1857 first erupted against British colonial rule.
-
D.
Gurugram
Gurugram is a major financial and technology hub in the Indian state of Haryana, known for its modern skyline, multinational corporate offices, and proximity to New Delhi.
-
E.
Ambala
Ambala is a historic city and important military and transportation hub in the northern Indian state of Haryana.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a518e6348190b467c2fab3fd1f11 |
completed | March 1, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6ef9b97881908eab2a5472b02183 |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:36 p.m.