Triple
T3913362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dewey |
E87376
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Culebra |
E2678
|
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: Culebra | Statement: [Dewey, locatedIn, Culebra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Culebra Context triple: [Dewey, locatedIn, Culebra]
-
A.
Culebra
chosen
Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
-
B.
Culebrita
Culebrita is a small, uninhabited cay off the coast of Culebra, Puerto Rico, known for its pristine beaches, clear waters, and historic lighthouse.
-
C.
Bois Caïman
Bois Caïman is a historic site in northern Haiti renowned as the location of the 1791 Vodou ceremony that helped spark the Haitian Revolution.
-
D.
Mocorito
Mocorito is a historic town and municipality in the Mexican state of Sinaloa, known for its colonial architecture and cultural traditions.
-
E.
Ciluba
Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed37b19c81908e690c495d96607f |
completed | March 9, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5285c52808190b9cbb2e3e03a18cb |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:22 p.m.