Triple
T20282565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ajit Singh |
E503186
|
entity |
| Predicate | ethnicGroup |
P194
|
FINISHED |
| Object | Jat |
—
|
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: Jat | Statement: [Ajit Singh, ethnicGroup, Jat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jat Context triple: [Ajit Singh, ethnicGroup, Jat]
-
A.
Jat
chosen
Jat is a traditionally agrarian, martial, and landowning community primarily found in northern India and Pakistan, known for its significant cultural and political influence in the region.
-
B.
JAT
JAT is the station code for Jammu Tawi railway station, a major rail hub serving the city of Jammu in the Indian union territory of Jammu and Kashmir.
-
C.
Arajet
Arajet is a Dominican low-cost airline based in Santo Domingo that operates flights across the Caribbean and the Americas.
-
D.
Aerei
Aerei is a conceptual artwork series by Italian artist Alighiero Boetti featuring intricate maps of the world overlaid with numerous airplanes in flight.
-
E.
Jais Flight
Jais Flight is a record-breaking zipline attraction on Jebel Jais in Ras Al Khaimah, United Arab Emirates, known for its extreme length and high-speed descent.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6768f86448190842389a98b93a918 |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 10:40 a.m.