Triple
T18488570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who Do You Think You Are? |
E451753
|
entity |
| Predicate | hasProtagonistFrom |
P8706
|
FINISHED |
| Object | small-town Ontario |
—
|
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: small-town Ontario | Statement: [Who Do You Think You Are?, hasProtagonistFrom, small-town Ontario]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistFrom Context triple: [Who Do You Think You Are?, hasProtagonistFrom, small-town Ontario]
-
A.
hasProtagonist
chosen
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
hasProtagonistFromSource
Indicates that a work’s main character originates from, or is derived from, a specified source (such as another work, franchise, or medium).
-
C.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
D.
protagonistBasedOn
Indicates that a fictional work’s main character is modeled on, inspired by, or derived from a particular real or fictional person or entity.
-
E.
hasProtagonistInFirstVolume
Indicates that a work’s first volume features a specific entity as its main character.
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e531d8bac4819099306abbf78b9565 |
completed | April 19, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:35 a.m.