Triple
T7622791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hahn |
E172540
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Haan |
E172540
|
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: Haan | Statement: [Hahn, hasVariant, Haan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haan Context triple: [Hahn, hasVariant, Haan]
-
A.
Haenam
Haenam is a coastal county in South Jeolla Province, South Korea, known for being the country's southernmost mainland point and for its scenic agricultural landscapes.
-
B.
Hahn
chosen
Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
-
C.
Haya
Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
-
D.
Han
Han refers to the majority ethnic group in China, historically associated with Chinese civilization, language, and culture.
-
E.
Han
Han is a common transliteration of the historical Central Asian title "Khan," often associated with rulers and nobility in various Turkic and Mongolic cultures.
- 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_69c699506b308190826894dab1d9ea86 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa65309c8190b95b894c051b003d |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870a00f8c8190935ee9b3054ada90 |
completed | March 29, 2026, 12:21 a.m. |
Created at: March 27, 2026, 3:56 p.m.