Triple
T17982301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vishva Hindu Parishad |
E449630
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | VHP |
—
|
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: VHP | Statement: [Vishva Hindu Parishad, shortName, VHP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VHP Context triple: [Vishva Hindu Parishad, shortName, VHP]
-
A.
VHP
chosen
VHP is a right-wing Hindu nationalist organization in India known for its role in promoting Hindutva ideology and involvement in religious and political campaigns.
-
B.
VHP UK
VHP UK is the United Kingdom branch of the Vishva Hindu Parishad, a Hindu nationalist organization focused on promoting Hindu religious, cultural, and social interests among the diaspora.
-
C.
VHP of America
VHP of America is the United States-based branch of the Vishva Hindu Parishad, focused on promoting Hindu religious, cultural, and social activities among the Indian diaspora.
-
D.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
E.
FHP
FHP is the state law enforcement agency responsible for highway safety and traffic enforcement across Florida’s roadways.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b297b7108190a676409b330ca23b |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 10, 2026, 10:22 a.m.