Triple
T7584555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Ariel |
E179573
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Ariel |
E645024
|
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: Ariel | Statement: [Operation Ariel, namedAfter, Ariel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ariel Context triple: [Operation Ariel, namedAfter, Ariel]
-
A.
Ariel
Ariel is a posthumously published poetry collection by Sylvia Plath that is widely regarded as her most powerful and influential work.
-
B.
Ariel
Ariel is one of Uranus's major icy moons, known for its relatively bright surface and complex system of canyons and fault valleys.
-
C.
Ariel
Ariel is the adventurous, red-haired mermaid princess from Disney’s The Little Mermaid, known for her curiosity about the human world and iconic songs like “Part of Your World.”
-
D.
Ariel
Ariel is a leading global laundry detergent brand known for its stain-removal performance and wide range of fabric care products.
-
E.
Ariel
chosen
Ariel is a large Israeli settlement city in the central West Bank, known for its significant population, industrial zone, and the presence of Ariel University.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f993cd0c8190864f801074625a32 |
completed | March 27, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c861812e08819097fd14fe2b8fee13 |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:52 p.m.