Triple
T20851074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shahpur subdivision |
E513363
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object | Shahpur |
—
|
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: Shahpur | Statement: [Shahpur subdivision, administrativeCentre, Shahpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shahpur Context triple: [Shahpur subdivision, administrativeCentre, Shahpur]
-
A.
Shahpur
chosen
Shahpur is a notable town in Bihar, India, recognized as one of the main urban centers of Bhojpur district.
-
B.
Shapurji
Shapurji is the given name of Shapurji Saklatvala, a prominent early 20th-century British Communist politician of Indian Parsi origin.
-
C.
Goshtasp
Goshtasp is a legendary Kayanian king in Persian mythology, best known as the father of the hero Esfandiyar and a patron of Zoroaster.
-
D.
Khusrav
Khusrav is a masculine given name of Persian origin, historically borne by princes and notable figures in Central and South Asia.
-
E.
Khosrowshahi
Khosrowshahi is a Persian surname most prominently associated with Dara Khosrowshahi, the Iranian-American business executive and CEO of Uber.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3a3d8808190b8efce77ae36850e |
completed | April 21, 2026, 12:24 a.m. |
Created at: April 16, 2026, 12:43 p.m.