Triple
T1176946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uranus |
E25048
|
entity |
| Predicate | bloodProduced |
P26257
|
FINISHED |
| Object | Meliae |
E89174
|
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: Meliae | Statement: [Uranus, bloodProduced, Meliae]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meliae Context triple: [Uranus, bloodProduced, Meliae]
-
A.
Meliae
chosen
The Meliae are nymphs from Greek mythology associated with ash trees and often linked to the early generations of humanity and rustic woodland life.
-
B.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
C.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
D.
Zimeysa
Zimeysa is a railway station in the canton of Geneva, Switzerland, serving local and regional train services on the Geneva–La Plaine line.
-
E.
Enodia
Enodia is an epithet of the Greek goddess Hecate that emphasizes her role as a protector and guide along roads, thresholds, and liminal spaces.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bf15423481909cb3e661e58d3d94 |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0146e1ec8190974e9d73acd6ca90 |
completed | March 8, 2026, 4:55 a.m. |
Created at: March 1, 2026, 7:45 p.m.