Triple
T8788783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hilary Hahn |
E209108
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hahn |
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: Hahn | Statement: [Hilary Hahn, familyName, Hahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hahn Context triple: [Hilary Hahn, familyName, Hahn]
-
A.
Hahn
chosen
Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
-
B.
Hansi
Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
-
C.
Hauke
Hauke is a Germanic given name, particularly common in Northern Germany, that is cognate with the English name Hugh.
-
D.
Hanem
Hanem is an Ottoman-era honorific title used for women of high social standing, similar to "lady" or "madam."
-
E.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f8b0c108190af53d4bb9b132c5c |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f493f648190b0e9392f1abb44a1 |
completed | April 3, 2026, 7:42 a.m. |
Created at: March 30, 2026, 6:43 p.m.