Triple
T15420553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lighthouse Point |
E369363
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Santa Cruz |
unclear NED1
|
NE FINISHED |
How this triple was built (2 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: [Lighthouse Point, locatedIn, Santa Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz Context triple: [Lighthouse Point, locatedIn, 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.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (3 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_69ff1a7adb848190836fb972bc8744f1 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:20 a.m.