Triple
T22008729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobi |
E543518
|
entity |
| Predicate | shortFormOf |
P43
|
FINISHED |
| Object | Tobias |
—
|
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: Tobias | Statement: [Tobi, shortFormOf, Tobias]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tobias Context triple: [Tobi, shortFormOf, Tobias]
-
A.
Tobias
Tobias is the virtuous young protagonist of the biblical Book of Tobit, known for his journey with the angel Raphael and the healing of his father’s blindness.
-
B.
Tobias
Tobias is the full given name of Toby Ziegler, the fictional White House Communications Director from the television series "The West Wing."
-
C.
Tobias
Tobias is a character from the novel "Watch Over Me," playing a significant role in the story's emotional and psychological development.
-
D.
Tobias
Tobias is a surname of likely Hebrew origin, borne by various notable individuals including the American character actor George Tobias.
-
E.
Tobias
Tobias is a character in the third act of a dramatic work, likely serving a pivotal role in the act’s unfolding conflict and resolution.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a2aebc8190951ee0bf9fd8e16d |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:21 p.m.