Triple
T22728645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GWL |
E562065
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Gwalior |
—
|
NE NERFINISHED |
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: Gwalior | Statement: [GWL, cityServed, Gwalior]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwalior Context triple: [GWL, cityServed, Gwalior]
-
A.
Gwalior
chosen
Gwalior is a historic city in the Indian state of Madhya Pradesh, renowned for its hilltop fort, rich royal heritage, and cultural significance.
-
B.
Indore
Indore is a major commercial and educational hub in central India, known for its vibrant markets, food culture, and rapidly growing urban infrastructure.
-
C.
Jabalpur
Jabalpur is a major city in the central Indian state of Madhya Pradesh, known for its industrial base, educational institutions, and nearby marble rock formations along the Narmada River.
-
D.
Bhilsa
Bhilsa is a historical town in the Vidisha district of Madhya Pradesh, India, known for its ancient Buddhist and Hindu archaeological sites.
-
E.
Jhansi
Jhansi is a historic city in northern India, renowned for its strategic fort and its central role in the 1857 uprising against British colonial rule.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1792b22cc819099aa00bb2dbacce3 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:21 p.m.