Triple
T22924278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khajuraho (Lok Sabha constituency) |
E569254
|
entity |
| Predicate | hasAssemblySegments |
P63908
|
FINISHED |
| Object | Hatta |
—
|
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: Hatta | Statement: [Khajuraho (Lok Sabha constituency), hasAssemblySegments, Hatta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hatta Context triple: [Khajuraho (Lok Sabha constituency), hasAssemblySegments, Hatta]
-
A.
Hatta
Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
-
B.
Hatta
chosen
Hatta is a prominent town in the Damoh district of Madhya Pradesh, India, known as a local commercial and administrative center.
-
C.
Haruru
Haruru is a small settlement in New Zealand’s Bay of Islands region, known for its scenic surroundings and proximity to Haruru Falls.
-
D.
Moru
Moru is a Central Sudanic language spoken primarily by the Moru people in South Sudan.
-
E.
Kahama
Kahama is a town and district-level administrative center in northwestern Tanzania known for its mining activities and role as a commercial hub in the Shinyanga area.
- 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d7973c8190b09a5690fd1d3f28 |
completed | April 29, 2026, 3:53 a.m. |
Created at: April 17, 2026, 3:43 p.m.