Triple
T15693657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moster |
E380399
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Moster Amfi |
E380399
|
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: Moster Amfi | Statement: [Moster, hasLandmark, Moster Amfi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moster Amfi Context triple: [Moster, hasLandmark, Moster Amfi]
-
A.
Moster
chosen
Moster is an island in the municipality of Bømlo in Vestland county, Norway, known for its historic church and role in early Norwegian Christianity.
-
B.
Munttoren
Munttoren is a historic clock and bell tower in central Amsterdam, originally part of the city’s medieval fortifications and now a notable canal-side landmark.
-
C.
Olbrzym
Olbrzym is the pseudonym of Henryk Humięcki, under which he is known in his public and creative activities.
-
D.
Gigandet
Gigandet is the surname of American actor Cam Gigandet, known for his roles in films like "Twilight" and "Never Back Down."
-
E.
Mosen
Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4f5a888190bd3681bcb9bbc02f |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6eed9a8c8190a57ffce61a27ec17 |
completed | May 9, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:44 a.m.