Triple
T13058205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Han |
E327631
|
entity |
| Predicate | relatedTitle |
P914
|
FINISHED |
| Object | Beg |
E468615
|
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: Beg | Statement: [Han, relatedTitle, Beg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beg Context triple: [Han, relatedTitle, Beg]
-
A.
Beg
chosen
Beg is a historical Turkic and Central Asian noble title denoting a chieftain, lord, or high-ranking official.
-
B.
BEG
BEG is the IATA airport code for Belgrade Nikola Tesla Airport, the main international airport serving Serbia’s capital city.
-
C.
Begnins
Begnins is a small municipality in the canton of Vaud in western Switzerland, situated in the La Côte wine-growing region between Lake Geneva and the Jura Mountains.
-
D.
Beg for It
"Beg for It" is a hip hop single by Australian rapper Iggy Azalea featuring Danish singer MØ, known for its catchy hook and club-oriented production.
-
E.
Begging
"Begging" is a song by Nigerian singer Yemi Alade, known for its Afro-pop sound and themes of love and emotional vulnerability.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980be37208190962e91f1e19df159 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbe0bf3081909ff498ac66cb2aa6 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:58 p.m.