Triple
T13800035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisebergbanan |
E331614
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Zierer |
E25304
|
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: Zierer | Statement: [Lisebergbanan, manufacturer, Zierer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zierer Context triple: [Lisebergbanan, manufacturer, Zierer]
-
A.
Zierer
chosen
Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
-
B.
Hirzer
Hirzer is a prominent mountain peak in the Sarntal Alps of South Tyrol, Italy, known for its panoramic hiking routes and scenic alpine views.
-
C.
Zerbe
Zerbe is a surname of German origin borne by various notable individuals, including American actor Anthony Zerbe.
-
D.
Zurer
Zurer is the surname of Ayelet Zurer, an Israeli actress known for her roles in international films and television series.
-
E.
Loerzer
Loerzer is the surname of Bruno Loerzer, a notable German First World War flying ace and later Luftwaffe general.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ce9148190b23370f6a522ff7a |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0893a20819081d4001b8dbc9c36 |
completed | May 3, 2026, 8:31 p.m. |
Created at: April 9, 2026, 10:11 p.m.