Triple
T7166157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyderabad Division |
E167072
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Badin |
E646241
|
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: Badin | Statement: [Hyderabad Division, hasMajorCity, Badin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badin Context triple: [Hyderabad Division, hasMajorCity, Badin]
-
A.
Badin District
chosen
Badin District is an administrative district in the Sindh province of Pakistan, known for its coastal location along the Arabian Sea and its agriculture-based economy.
-
B.
Eastland
Eastland is a surname most notably associated with James Eastland, a long-serving and influential U.S. senator from Mississippi.
-
C.
Tell City
Tell City is a small riverside community in southern Indiana known for its Swiss-German heritage and historic furniture-making industry.
-
D.
Cudahy
Cudahy is a small, densely populated city in southeastern Los Angeles County, California, known for its predominantly Latino community and urban residential character.
-
E.
Bayfield
Bayfield is a residential suburb of the historic town of Chepstow in Monmouthshire, Wales.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e85a07388190a07054ef12870fa1 |
completed | March 27, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b901cb608190acd25c22b38a1957 |
completed | March 28, 2026, 11:18 a.m. |
Created at: March 27, 2026, 2:48 p.m.