Triple
T38123147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabard Inn, Southwark |
E951994
|
entity |
| Predicate | mediumOfMostFamousDepiction |
P102251
|
FINISHED |
| Object | poetry |
—
|
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: poetry | Statement: [Tabard Inn, Southwark, mediumOfMostFamousDepiction, poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediumOfMostFamousDepiction Context triple: [Tabard Inn, Southwark, mediumOfMostFamousDepiction, poetry]
-
A.
commonlyDepictedOn
Indicates that something is frequently shown or represented on the surface, medium, or context of another thing.
-
B.
primaryMediumOfDepiction
Indicates that a specified medium (such as painting, sculpture, or photography) is the main form through which an entity is depicted.
-
C.
mediumOfFame
chosen
Indicates the medium, field, or domain through which an entity became famous or gained public recognition.
-
D.
depictsMedium
Indicates that one entity visually represents or portrays the medium or material of another entity.
-
E.
notableForDepicting
Indicates that something is recognized or distinguished specifically for portraying or representing a particular subject, theme, or scene.
- 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.