Triple
T7483876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomorrowland |
E176829
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Orbitron
Orbitron is a retro-futuristic spinning rocket ride in Disneyland’s Tomorrowland that lets guests pilot spacecraft high above the land.
|
E667048
|
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: Orbitron | Statement: [Tomorrowland, hasAttraction, Orbitron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orbitron Context triple: [Tomorrowland, hasAttraction, Orbitron]
-
A.
Orb
The Orb is a river in southern France that flows through the Occitanie region before emptying into the Mediterranean Sea.
-
B.
Orb
The Orb is a ceremonial piece of royal regalia symbolizing monarchical authority and Christian sovereignty, traditionally held by the monarch during British coronations.
-
C.
Orb
Orb is a biometric imaging device developed for the Worldcoin project that scans people’s irises to create unique digital identities.
-
D.
Orbital
Orbital is a British electronic music duo known for their influential role in the 1990s rave and techno scenes and their complex, layered compositions.
-
E.
Orbit
Orbit is a popular brand of sugar-free chewing gum produced by the Wrigley Company, known for its variety of flavors and emphasis on oral health.
- 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: Orbitron Triple: [Tomorrowland, hasAttraction, Orbitron]
Generated description
Orbitron is a retro-futuristic spinning rocket ride in Disneyland’s Tomorrowland that lets guests pilot spacecraft high above the land.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orbitron Target entity description: Orbitron is a retro-futuristic spinning rocket ride in Disneyland’s Tomorrowland that lets guests pilot spacecraft high above the land.
-
A.
Orb
The Orb is a river in southern France that flows through the Occitanie region before emptying into the Mediterranean Sea.
-
B.
Orb
Orb is a biometric imaging device developed for the Worldcoin project that scans people’s irises to create unique digital identities.
-
C.
Orb
The Orb is a ceremonial piece of royal regalia symbolizing monarchical authority and Christian sovereignty, traditionally held by the monarch during British coronations.
-
D.
Orbital
Orbital is a British electronic music duo known for their influential role in the 1990s rave and techno scenes and their complex, layered compositions.
-
E.
Orbit
Orbit is a publishing imprint best known for releasing science fiction and fantasy books.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f53923e4819081bf79ed962a971c |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8349d83cc8190af98c3212e28e913 |
completed | March 28, 2026, 8:05 p.m. |
| NEDg | Description generation | batch_69c835916e948190ad5789e4611f8842 |
completed | March 28, 2026, 8:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83635c7888190834f02e7ea0f1ab5 |
completed | March 28, 2026, 8:12 p.m. |
Created at: March 27, 2026, 3:42 p.m.