Triple
T17526437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sea Beggars |
E426807
|
entity |
| Predicate | captured |
P4236
|
FINISHED |
| Object | Brielle |
—
|
NE NERFINISHED |
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: Brielle | Statement: [Sea Beggars, captured, Brielle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brielle Context triple: [Sea Beggars, captured, Brielle]
-
A.
Brielle
chosen
Brielle is a historic fortified town in the Dutch province of South Holland, known for its well-preserved medieval center and role in the Eighty Years' War.
-
B.
Rainelle
Rainelle is a small town located in western Greenbrier County, West Virginia, historically tied to the lumber industry and the surrounding Appalachian region.
-
C.
Baylene
Baylene is an elderly, wise brachiosaurus who serves as a gentle mentor figure in Disney's 2000 animated film "Dinosaur."
-
D.
Brinley
Brinley is a given name most notably borne by Brinley Newton-John, the British-born Australian professor and father of singer Olivia Newton-John.
-
E.
Bree
Bree is a central character in the science-fiction film "Transcendence," closely connected to the story’s exploration of artificial intelligence and technological ethics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d6a2548190acf26f2d5d4aab66 |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.