Triple
T4908015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gatchina Palace |
E109959
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Arsenal Wing
Arsenal Wing is a section of Gatchina Palace historically used for storing and displaying weapons and military equipment.
|
E478515
|
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: Arsenal Wing | Statement: [Gatchina Palace, hasPart, Arsenal Wing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arsenal Wing Context triple: [Gatchina Palace, hasPart, Arsenal Wing]
-
A.
Arsenalna
Arsenalna is a Kyiv Metro station best known for being one of the deepest underground metro stations in the world.
-
B.
Rakhiot Flank
Rakhiot Flank is a prominent route and face on Nanga Parbat, known historically as the line of the mountain’s first successful ascent.
-
C.
Ewbank
Ewbank is a surname most notably associated with Weeb Ewbank, a Hall of Fame American football coach.
-
D.
Wingate
Wingate is a surname most notably associated with Orde Charles Wingate, an unconventional and influential British Army officer of the early 20th century.
-
E.
Richelieu Wing
The Richelieu Wing is a major section of the Louvre Museum that houses collections such as French sculpture, decorative arts, and Near Eastern antiquities in a historic palace setting.
- 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: Arsenal Wing Triple: [Gatchina Palace, hasPart, Arsenal Wing]
Generated description
Arsenal Wing is a section of Gatchina Palace historically used for storing and displaying weapons and military equipment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arsenal Wing Target entity description: Arsenal Wing is a section of Gatchina Palace historically used for storing and displaying weapons and military equipment.
-
A.
Arsenalna
Arsenalna is a Kyiv Metro station best known for being one of the deepest underground metro stations in the world.
-
B.
Rakhiot Flank
Rakhiot Flank is a prominent route and face on Nanga Parbat, known historically as the line of the mountain’s first successful ascent.
-
C.
Ewbank
Ewbank is a surname most notably associated with Weeb Ewbank, a Hall of Fame American football coach.
-
D.
Wingate
Wingate is a surname most notably associated with Orde Charles Wingate, an unconventional and influential British Army officer of the early 20th century.
-
E.
Richelieu Wing
The Richelieu Wing is a major section of the Louvre Museum that houses collections such as French sculpture, decorative arts, and Near Eastern antiquities in a historic palace setting.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e7452d481909078a0027e2a4566 |
completed | March 20, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fe098b081908e17d6d349b76364 |
completed | March 21, 2026, 10:16 a.m. |
| NEDg | Description generation | batch_69be7095dc8c8190bdda64e99232fe1e |
completed | March 21, 2026, 10:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be710df238819085b0a873e23ecfd9 |
completed | March 21, 2026, 10:21 a.m. |
Created at: March 20, 2026, 1:29 p.m.