Triple
T4014582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gard |
E90724
|
entity |
| Predicate | containsLandmark |
P1098
|
FINISHED |
| Object |
Tour Magne
Tour Magne is an ancient Roman watchtower in Nîmes, France, notable as one of the city’s most prominent historical monuments.
|
E405634
|
NE FINISHED |
How this triple was built (4 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: Tour Magne | Statement: [Gard, containsLandmark, Tour Magne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tour Magne Context triple: [Gard, containsLandmark, Tour Magne]
-
A.
Tour Voile
Tour Voile is a prominent annual offshore sailing race in France featuring multihull and monohull competitions along the French coastline.
-
B.
Tour Ronde
Tour Ronde is a prominent granite peak in the Mont Blanc massif of the Alps, popular with climbers for its accessible mixed routes and panoramic views.
-
C.
Tour Totem
Tour Totem is a modern high-rise residential and office building located in Paris’s Grenelle district near the Seine.
-
D.
Tour Tanguy
Tour Tanguy is a medieval tower in Brest, France, now serving as a local history museum showcasing the city’s past.
-
E.
Tour Perret
Tour Perret is a prominent modernist high-rise tower in Amiens, France, known as one of the country’s earliest skyscrapers and a key feature of the city’s skyline.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tour Magne Triple: [Gard, containsLandmark, Tour Magne]
Generated description
Tour Magne is an ancient Roman watchtower in Nîmes, France, notable as one of the city’s most prominent historical monuments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tour Magne Target entity description: Tour Magne is an ancient Roman watchtower in Nîmes, France, notable as one of the city’s most prominent historical monuments.
-
A.
Tour Voile
Tour Voile is a prominent annual offshore sailing race in France featuring multihull and monohull competitions along the French coastline.
-
B.
Tour Ronde
Tour Ronde is a prominent granite peak in the Mont Blanc massif of the Alps, popular with climbers for its accessible mixed routes and panoramic views.
-
C.
Tour Totem
Tour Totem is a modern high-rise residential and office building located in Paris’s Grenelle district near the Seine.
-
D.
Tour Tanguy
Tour Tanguy is a medieval tower in Brest, France, now serving as a local history museum showcasing the city’s past.
-
E.
Tour Perret
Tour Perret is a prominent modernist high-rise tower in Amiens, France, known as one of the country’s earliest skyscrapers and a key feature of the city’s skyline.
- F. None of above. chosen
Provenance (5 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8ad6348190b71feaf8c18c90c2 |
completed | March 9, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c73e6048190a59a8d8bc12c907d |
completed | March 14, 2026, 11:54 a.m. |
| NEDg | Description generation | batch_69b54d197f948190b751561da497fa9e |
completed | March 14, 2026, 11:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b54da5ee8c8190ae7c2757a8d1c204 |
completed | March 14, 2026, 11:59 a.m. |
Created at: March 9, 2026, 3:35 p.m.