Triple
T12245370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herbert Lange |
E291837
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lange |
E92052
|
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: Lange | Statement: [Herbert Lange, familyName, Lange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lange Context triple: [Herbert Lange, familyName, Lange]
-
A.
Lange
chosen
Lange is a German surname borne by numerous notable individuals across fields such as science, politics, arts, and sports.
-
B.
Langer
Langer is a surname most notably associated with Robert Langer, a pioneering American chemical engineer and prolific inventor in biotechnology and drug delivery.
-
C.
Longo
Longo is an Italian surname borne by various notable figures in politics, arts, and sports.
-
D.
Langebrug
Langebrug is a historic bridge spanning the Spaarne River in the Dutch city of Haarlem.
-
E.
Lansen
Lansen is the NATO reporting name for the Swedish Saab 32, a Cold War-era jet aircraft used primarily for attack and reconnaissance roles.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb893a08190bbdfcb23082b8f34 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60ab7b9308190b621b71d75aa10cc |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:51 p.m.