Triple
T1595851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin Court Underground Museum |
E34280
|
entity |
| Predicate | subjectOfDisplay |
P450
|
FINISHED |
| Object | life of Benjamin Franklin |
—
|
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: life of Benjamin Franklin | Statement: [Franklin Court Underground Museum, subjectOfDisplay, life of Benjamin Franklin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOfDisplay Context triple: [Franklin Court Underground Museum, subjectOfDisplay, life of Benjamin Franklin]
-
A.
subjectOfFilm
Indicates that a person, character, or topic is the main focus or central topic depicted in a particular film.
-
B.
displays
Indicates that one entity visually presents or shows another entity’s content or information.
-
C.
presentedBy
Indicates that something (such as an event, performance, or work) is formally organized, hosted, or introduced by a particular person or entity.
-
D.
displayedWith
Indicates that one entity is shown or presented together alongside another entity in the same context or view.
-
E.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a916d413f08190a4e137e5ed262e25 |
completed | March 5, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69a907bfb39c8190a31e0be14d3d52e6 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.