Triple
T619375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaia |
E14477
|
entity |
| Predicate | epithet |
P743
|
FINISHED |
| Object | Mother Earth |
E14477
|
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: Mother Earth | Statement: [Gaia, epithet, Mother Earth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mother Earth Context triple: [Gaia, epithet, Mother Earth]
-
A.
Gaia
chosen
Gaia is the primordial Greek earth goddess, revered as the ancestral mother of all life and the personification of the Earth itself.
-
B.
Earth
Earth is the third planet from the Sun and the only known world to support life, characterized by vast oceans, diverse ecosystems, and a protective atmosphere.
-
C.
Urana
Urana is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural surroundings and historic country character.
-
D.
Mondas
Mondas is the fictional twin planet of Earth in the Doctor Who universe, known as the original home of the Cybermen.
-
E.
Great Mother
Great Mother is an epithet of Gaia that emphasizes her role as the primordial earth goddess and universal mother figure in Greek mythology.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e25956c8190a1eed87002548658 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a563c682f88190a2af1087246be4c4 |
completed | March 2, 2026, 10:17 a.m. |
Created at: March 1, 2026, 7:35 p.m.