Triple
T13811346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oculus Quest |
E331896
|
entity |
| Predicate | codename |
P2980
|
FINISHED |
| Object |
Santa Cruz
Santa Cruz was the internal codename for Oculus’s standalone virtual reality headset that later became known as the Oculus Quest.
|
E1064469
|
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: Santa Cruz | Statement: [Oculus Quest, codename, Santa Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz Context triple: [Oculus Quest, codename, Santa Cruz]
-
A.
Santa Cruz
Santa Cruz is a coastal municipality in the Philippine island province of Marinduque known for its fishing communities and rural island-barangays.
-
B.
Santa Cruz
Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
-
C.
Santa Cruz
Santa Cruz is a municipality in the Brazilian state of Rio Grande do Norte, known for its religious tourism and the large statue of Santa Rita de Cássia.
-
D.
Santa Cruz
Saint Croix is the largest of the U.S. Virgin Islands in the Caribbean, known for its colonial history, beaches, and coral reefs.
-
E.
Santa Cruz
Santa Cruz is a coastal parish in the municipality of Santiago do Cacém in Portugal, known for its Atlantic beaches and seaside tourism.
- 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: Santa Cruz Triple: [Oculus Quest, codename, Santa Cruz]
Generated description
Santa Cruz was the internal codename for Oculus’s standalone virtual reality headset that later became known as the Oculus Quest.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz Target entity description: Santa Cruz was the internal codename for Oculus’s standalone virtual reality headset that later became known as the Oculus Quest.
-
A.
Santa Cruz
Santa Cruz is a coastal city in central California known for its beaches, boardwalk amusement park, and the University of California, Santa Cruz campus.
-
B.
Santa Cruz
Santa Cruz is a coastal municipality in the province of Davao del Sur in the Philippines, known for its mix of agricultural lands and growing eco-tourism attractions.
-
C.
Santa Cruz
Santa Cruz is a large, predominantly residential neighborhood located in the western part of Rio de Janeiro, Brazil, known for its industrial areas and historical sites.
-
D.
Santa Cruz
Santa Cruz is a coastal parish in the municipality of Santiago do Cacém in Portugal, known for its Atlantic beaches and seaside tourism.
-
E.
Santa Cruz
Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026ff6b481908066d6bf27064417 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8dc1ec0819098c4f32eb3991613 |
completed | May 3, 2026, 9:06 p.m. |
| NEDg | Description generation | batch_69f7ba6558fc819082dae55863a9a3b1 |
completed | May 3, 2026, 9:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7bb15d31c81909959e50219c4d905 |
completed | May 3, 2026, 9:16 p.m. |
Created at: April 9, 2026, 10:12 p.m.