Triple
T16348079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butte du Lion de Waterloo |
E396985
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Butte du Lion |
E396984
|
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: Butte du Lion | Statement: [Butte du Lion de Waterloo, alsoKnownAs, Butte du Lion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Butte du Lion Context triple: [Butte du Lion de Waterloo, alsoKnownAs, Butte du Lion]
-
A.
Butte du Lion
chosen
Butte du Lion is a large conical memorial mound in Waterloo, Belgium, topped by a cast-iron lion statue commemorating the Battle of Waterloo.
-
B.
Tête de Chien promontory
Tête de Chien promontory is a prominent rocky headland on the French Riviera overlooking Monaco and the Mediterranean Sea.
-
C.
Mont Dauban
Mont Dauban is the tallest mountain on Silhouette Island in the Seychelles, known for its lush tropical forests and panoramic views over the Indian Ocean.
-
D.
Mont-Oriol
Mont-Oriol is a novel by French writer Guy de Maupassant that satirically explores love, ambition, and the commercialization of a spa town in 19th-century France.
-
E.
Moncontour
Moncontour is a historic hilltop town in Brittany, northwestern France, renowned for its well-preserved medieval architecture and fortified walls.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da10ef64819092633e8b32e98f5d |
completed | April 18, 2026, 1:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002db40e0481908d919f2285e48a23 |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:07 a.m.