Triple
T14144999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alps four-thousanders |
E350521
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Lagginhorn |
E147698
|
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: Lagginhorn | Statement: [Alps four-thousanders, hasMember, Lagginhorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lagginhorn Context triple: [Alps four-thousanders, hasMember, Lagginhorn]
-
A.
Lagginhorn
chosen
Lagginhorn is a prominent 4,000-meter-class mountain in the Swiss Pennine Alps, known for its relatively accessible routes and panoramic views over the surrounding Valais peaks.
-
B.
Kuglhorn
Kuglhorn is a prominent mountain peak located near Tysfjord in Nordland county, northern Norway, known for its striking alpine scenery.
-
C.
Hornschuch
Hornschuch is a German surname most notably associated with Karl Georg Hornschuch, a 19th-century botanist and bryologist.
-
D.
Hattrop
Hattrop is a small village and district within the town of Soest in North Rhine-Westphalia, Germany.
-
E.
Tackley
Tackley is a rural village in Oxfordshire, England, known for its traditional English countryside setting and historic character.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61214de081909a5186ff11336f97 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf1b8508819096d4f5cf1456edca |
completed | May 7, 2026, 6:51 p.m. |
Created at: April 10, 2026, 12:53 a.m.