Triple
T6977788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Gunton |
E161756
|
entity |
| Predicate | producerOf |
P490
|
FINISHED |
| Object | The Green Planet |
E119217
|
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: The Green Planet | Statement: [Mike Gunton, producerOf, The Green Planet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Green Planet Context triple: [Mike Gunton, producerOf, The Green Planet]
-
A.
The Green Planet
chosen
The Green Planet is a BBC nature documentary series that explores the hidden life, behavior, and ecological importance of plants around the world.
-
B.
Sunny Earth
"Sunny Earth" is a track by Greek composer Vangelis from his 1998 electronic and ambient album "Earth."
-
C.
The Living Planet
The Living Planet is a landmark BBC nature documentary series presented by David Attenborough that explores the diversity of life and the ecosystems of Earth.
-
D.
A Perfect Planet
A Perfect Planet is a nature documentary series that explores how Earth's natural forces shape and sustain life across the globe.
-
E.
La Terre
La Terre is a naturalist novel by Émile Zola that portrays the brutal lives, struggles, and moral decay of French peasants in the 19th century countryside.
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db68d25c8190a1776908619ad979 |
completed | March 27, 2026, 7:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7754815c8819091d1291f7cdfec1d |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:31 p.m.