Triple
T12413700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Old Bedford |
E296581
|
entity |
| Predicate | depiction type |
P9800
|
FINISHED |
| Object | urban entertainment |
—
|
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: urban entertainment | Statement: [The Old Bedford, depiction type, urban entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depiction type Context triple: [The Old Bedford, depiction type, urban entertainment]
-
A.
depictionType
chosen
Indicates the specific manner or style in which something is visually represented or depicted.
-
B.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
-
C.
depictionPurpose
Indicates that one entity is depicted specifically for the purpose or function it serves in relation to another entity.
-
D.
depictionAction
Indicates an action in which one entity visually represents, illustrates, or portrays another entity.
-
E.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.