Triple
T9630672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Millerntor-Stadion |
E232794
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Reeperbahn |
E258700
|
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: Reeperbahn | Statement: [Millerntor-Stadion, locatedNear, Reeperbahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reeperbahn Context triple: [Millerntor-Stadion, locatedNear, Reeperbahn]
-
A.
Reeperbahn
chosen
Reeperbahn is Hamburg’s famous red-light and nightlife district street, known for its clubs, bars, theaters, and vibrant entertainment scene.
-
B.
Funken im Abgrund
Funken im Abgrund is a major autobiographical novel by Soma Morgenstern that portrays Jewish life in Eastern Europe and the collapse of the Austro-Hungarian world in the early 20th century.
-
C.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
D.
Blacker
Blacker is a comparative form of the color term "black," indicating a greater degree of darkness or blackness.
-
E.
Karmacoma
"Karmacoma" is a moody, trip hop track by Massive Attack known for its hypnotic beat, atmospheric production, and distinctive vocal delivery.
- 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_69ca848940cc8190b97cec654cb3bb4a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b01863c8190a9ec4684804f96bc |
completed | April 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d189f7ea448190b9fe123589a9f3c5 |
completed | April 4, 2026, 10 p.m. |
Created at: March 30, 2026, 8:11 p.m.