Triple
T5067329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neve Campbell |
E114175
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Neve |
E44196
|
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: Neve | Statement: [Neve Campbell, givenName, Neve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neve Context triple: [Neve Campbell, givenName, Neve]
-
A.
Neve
chosen
Neve is one of the official mascots of the 2006 Winter Olympics in Turin, depicted as a stylized snowball symbolizing winter sports and the spirit of the Games.
-
B.
Tennenlohe
Tennenlohe is a district of Erlangen in Bavaria, Germany, known for its proximity to research institutions and the Tennenlohe Forest nature reserve.
-
C.
Carbon Glacier
Carbon Glacier is a major valley glacier on the north slope of Mount Rainier in Washington, notable for its great thickness and low terminus elevation.
-
D.
White Glacier
White Glacier is a prominent glacier located on Mount Olympus, known for its extensive ice fields and alpine terrain.
-
E.
Mount Nivea
Mount Nivea is a prominent mountain peak that forms the highest point in the remote South Orkney Islands of the Southern Ocean.
- 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd749bf69c819093e75dce56f1c0ab |
completed | March 20, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea4a027a88190a515a374e5405d8a |
completed | March 21, 2026, 2:01 p.m. |
Created at: March 20, 2026, 1:38 p.m.