Triple
T10130747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanno Hahn |
E226330
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hanno |
E255182
|
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: Hanno | Statement: [Hanno Hahn, givenName, Hanno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanno Context triple: [Hanno Hahn, givenName, Hanno]
-
A.
Hanno
chosen
Hanno is a city in Saitama Prefecture, Japan, known for its natural scenery, hiking spots, and proximity to the Tokyo metropolitan area.
-
B.
Hannoa
Hannoa is a small genus of flowering plants in the quassia family Simaroubaceae, known for its tropical trees and shrubs often containing bitter compounds.
-
C.
Bahdini
Bahdini is a Northern Kurdish dialect spoken primarily in parts of Turkey and Iraq.
-
D.
Hannum
Hannum is a surname most notably associated with Alex Hannum, a Hall of Fame American basketball coach and former player.
-
E.
Hantes
Hantes is a river in Belgium and France that serves as a tributary of the Sambre.
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd33438988190be45878f98695816 |
completed | April 2, 2026, 2:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc7c50b08190a04aa2f58a6c300a |
completed | April 5, 2026, 8:56 p.m. |
Created at: March 30, 2026, 9:05 p.m.