Triple
T20293453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamsen Donner |
E510085
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Donner |
—
|
NE NERFINISHED |
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: Donner | Statement: [Tamsen Donner, familyName, Donner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donner Context triple: [Tamsen Donner, familyName, Donner]
-
A.
Donner
Donner is a superhero character from DC Comics' Dakotaverse (Milestone) imprint, typically depicted with metahuman abilities and appearing in stories set in the shared Dakota City universe.
-
B.
Donner
chosen
Donner is one of Santa Claus's traditional flying reindeer, often depicted as helping pull Santa’s sleigh on Christmas Eve.
-
C.
Karluk
Karluk refers to a historical branch of the Turkic peoples and their language group, influential in Central Asia during the early medieval period.
-
D.
Chisum
Chisum is a 1970 Western film starring John Wayne that dramatizes the Lincoln County War in New Mexico.
-
E.
Toussant
Toussant is the surname of Michel'le, the American R&B singer known for her distinctive high speaking voice and powerful singing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67704262c8190bc903b733d849881 |
completed | April 20, 2026, 6:57 p.m. |
Created at: April 16, 2026, 11:13 a.m.