Triple
T9350967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Hanau |
E225016
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Hanau |
E289017
|
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: Hanau | Statement: [County of Hanau, capital, Hanau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanau Context triple: [County of Hanau, capital, Hanau]
-
A.
Hanau
chosen
Hanau is a town in the German state of Hesse, known as an important regional center and the birthplace of the Brothers Grimm.
-
B.
Hanworth
Hanworth is a suburban residential area in west London, England, known for its parks, local amenities, and proximity to Heathrow Airport.
-
C.
Meerbusch
Meerbusch is a town in the German state of North Rhine-Westphalia, situated on the west bank of the Rhine near Düsseldorf and known for its affluent residential areas and green surroundings.
-
D.
Poppenhausen
Poppenhausen is a small German town located in the Schweinfurt administrative region of northern Bavaria.
-
E.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f9248c08190a7bb40feec2eb217 |
completed | April 1, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1525bd4e88190a62e5e383d1e786b |
completed | April 4, 2026, 6:03 p.m. |
Created at: March 30, 2026, 7:41 p.m.