Triple
T4013716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Nathan-Turner |
E90704
|
entity |
| Predicate | introducedCompanion |
P22642
|
FINISHED |
| Object | Nyssa |
E378476
|
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: Nyssa | Statement: [John Nathan-Turner, introducedCompanion, Nyssa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyssa Context triple: [John Nathan-Turner, introducedCompanion, Nyssa]
-
A.
Nyssa
chosen
Nyssa is a companion of the Fifth Doctor in the long-running British science fiction television series Doctor Who.
-
B.
Zelkova
Zelkova is a small genus of deciduous trees in the elm family, valued as ornamentals and for bonsai, and native to parts of Europe and Asia.
-
C.
Birch
Birch is a masculine given name most notably borne by American politician Birch Bayh, a long-serving U.S. senator from Indiana.
-
D.
Cornus
Cornus is a genus of woody plants commonly known as dogwoods, which includes numerous species valued for their ornamental flowers, colorful bracts, and attractive bark.
-
E.
Castanea
Castanea is a genus of deciduous trees and shrubs commonly known as chestnuts, valued for their edible nuts and durable timber.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01994b0c8190b34af36acadad5c6 |
completed | March 9, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c73e6048190a59a8d8bc12c907d |
completed | March 14, 2026, 11:54 a.m. |
Created at: March 9, 2026, 3:35 p.m.