Triple
T287892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman De Croo |
E5924
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Herman |
E31859
|
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: Herman | Statement: [Herman De Croo, givenName, Herman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herman Context triple: [Herman De Croo, givenName, Herman]
-
A.
Herman
chosen
Herman is a surname most notably associated with Edward S. Herman, an American economist, media analyst, and critic of U.S. foreign policy.
-
B.
Hermann
Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
-
C.
Harold
Harold is a masculine given name of Old English origin, historically borne by several notable figures including kings and modern public personalities.
-
D.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
-
E.
Erwin
Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e2f5c0081908e548b314f5e986d |
completed | Feb. 28, 2026, 3:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f0a0fd6081908b672fe7106a0c74 |
completed | March 1, 2026, 7:54 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.