Triple
T10565603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theodor Haak |
E249341
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Haak |
E243310
|
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: Haak | Statement: [Theodor Haak, familyName, Haak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haak Context triple: [Theodor Haak, familyName, Haak]
-
A.
Haak
chosen
Haak was the original publisher of the first edition of the influential botanical work "Genera Plantarum."
-
B.
Haken
Haken is a British progressive metal band known for its complex compositions, technical musicianship, and stylistic similarities to acts like Dream Theater.
-
C.
Hau
Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
-
D.
Haan
Haan is a town in the German state of North Rhine-Westphalia, known for its location between Düsseldorf and Wuppertal and its mix of residential areas and light industry.
-
E.
Hukkeri
Hukkeri is a town in the Indian state of Karnataka, known for its historical temples and its location within the Belagavi region.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ce78c8190bf3227053ef88a48 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9349bb7748190b5afb492e78d1128 |
completed | April 10, 2026, 5:34 p.m. |
Created at: April 6, 2026, 12:36 p.m.