Triple
T8295963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marina Wheeler |
E194217
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marina |
E270577
|
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: Marina | Statement: [Marina Wheeler, givenName, Marina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marina Context triple: [Marina Wheeler, givenName, Marina]
-
A.
Marina
Marina is a recurring comedic character in the long-running British sitcom "Last of the Summer Wine," known for her flirtatious relationship with the married Howard.
-
B.
Marina
chosen
Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
-
C.
Marina
Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
-
D.
Lissa
Lissa is a historic town in western Poland, known today as Leszno, that was once part of Germany and is notable as the birthplace of several prominent Jewish and intellectual figures.
-
E.
Kamarina
Kamarina is a modern settlement in the Epirus region of northwestern Greece, located near the archaeological site of ancient Cassope.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7df73d4c81909ad9cf0786eb5a20 |
completed | March 31, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd68a3258481908fe04fed1d00c9ba |
completed | April 1, 2026, 6:49 p.m. |
Created at: March 30, 2026, 5:53 p.m.