Triple
T15420748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surf City |
E369367
|
entity |
| Predicate | associatedWithCity |
P1481
|
FINISHED |
| Object |
Santa Cruz
Santa Cruz is a coastal California city famed for its laid-back surf culture, scenic beaches, and historic boardwalk.
|
E993464
|
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: [Surf City, associatedWithCity, Santa Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz Context triple: [Surf City, associatedWithCity, Santa Cruz]
-
A.
Santa Cruz
Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
-
B.
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.
-
C.
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.
-
D.
Santa Cruz
Santa Cruz is a coastal municipality in the Philippine island province of Marinduque known for its fishing communities and rural island-barangays.
-
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: [Surf City, associatedWithCity, Santa Cruz]
Generated description
Santa Cruz is a coastal California city famed for its laid-back surf culture, scenic beaches, and historic boardwalk.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz Target entity description: Santa Cruz is a coastal California city famed for its laid-back surf culture, scenic beaches, and historic boardwalk.
-
A.
Santa Cruz
chosen
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 notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
-
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 coastal municipality in the Philippine island province of Marinduque known for its fishing communities and rural island-barangays.
- F. None of above.
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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ebe7b1081908e6b9e6e128a8d5d |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff755ffbdc8190825010885e68ebc3 |
completed | May 9, 2026, 5:56 p.m. |
| NEDg | Description generation | batch_69ff7653ccc08190b4b44b4f55344f65 |
completed | May 9, 2026, 6 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff76d21a148190bbe66c3ff12386f3 |
completed | May 9, 2026, 6:02 p.m. |
Created at: April 10, 2026, 3:20 a.m.