Triple
T20744816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | post-war London |
E510549
|
entity |
| Predicate | memoryAndRepresentation |
P90996
|
FINISHED |
| Object | subject of social history studies |
—
|
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: subject of social history studies | Statement: [post-war London, memoryAndRepresentation, subject of social history studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memoryAndRepresentation Context triple: [post-war London, memoryAndRepresentation, subject of social history studies]
-
A.
memoryType
Indicates the specific category or kind of memory associated with an entity or process.
-
B.
builtInMemoryOf
Indicates that something was constructed as a tribute or commemoration to a particular person, group, or event.
-
C.
memoryState
Indicates the condition or configuration of an entity’s stored information at a particular point in time.
-
D.
memoryCharacteristic
Indicates a relationship where a specific property or quality is attributed to a memory or memory-related entity.
-
E.
representationIn
chosen
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
- 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c21197088190951a4c4a7e765891 |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:33 p.m.