Triple
T22396745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobie |
E553652
|
entity |
| Predicate | popularityComparedToToby |
P106096
|
FINISHED |
| Object | less common |
—
|
LITERAL 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: less common | Statement: [Tobie, popularityComparedToToby, less common]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularityComparedToToby Context triple: [Tobie, popularityComparedToToby, less common]
-
A.
relationshipWithTobyFlenderson
Indicates that one entity has some form of relationship, connection, or association with Toby Flenderson.
-
B.
popularityRelativeTo
chosen
Indicates how the popularity of one entity compares to the popularity of another entity, typically in terms of being more, less, or equally popular.
-
C.
relationshipToSirTobyBelch
Indicates that one entity has a specified familial, social, or interpersonal connection to the character Sir Toby Belch.
-
D.
relationshipToAgnesAndTobias
Indicates the specific familial, social, or other relational connection that an entity has to the pair Agnes and Tobias considered together.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- F. None of above.
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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585f67108190b8d3f23eaa0ed120 |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:45 p.m.