Triple
T16070988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Highway 9 (India) |
E389858
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Hazaribagh |
E321797
|
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: Hazaribagh | Statement: [National Highway 9 (India), connectsCity, Hazaribagh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hazaribagh Context triple: [National Highway 9 (India), connectsCity, Hazaribagh]
-
A.
Hazaribagh
chosen
Hazaribagh is a town in the Indian state of Jharkhand known for its scenic hills, pleasant climate, and proximity to Hazaribagh National Park.
-
B.
Bahadurabad
Bahadurabad is a prominent residential and commercial neighborhood in Karachi, Pakistan, known for its bustling markets, eateries, and central location within the city.
-
C.
Shahganj
Shahganj is a town in the Jaunpur district of Uttar Pradesh, India, known as a local commercial and transportation hub for the surrounding rural region.
-
D.
Hazratganj
Hazratganj is a historic and bustling commercial and cultural hub in Lucknow, known for its colonial-era architecture, shopping arcades, and vibrant street life.
-
E.
Nawabganj
Nawabganj is a town in the Indian state of Uttar Pradesh, known as one of the urban centers within Barabanki district.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183be909c8190ac6c37ab047151ae |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0025ef00548190b802b4aaba907aa2 |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 4:57 a.m.