Triple
T24809184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piers Dunkerley |
E620736
|
entity |
| Predicate | hasMemoryDedicatedIn |
P102936
|
FINISHED |
| Object | War Requiem |
—
|
NE NERFINISHED |
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: War Requiem | Statement: [Piers Dunkerley, hasMemoryDedicatedIn, War Requiem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemoryDedicatedIn Context triple: [Piers Dunkerley, hasMemoryDedicatedIn, War Requiem]
-
A.
hasMemoryIn
Indicates that an entity possesses or stores memory, information, or experiences within a specified context, location, or medium.
-
B.
hasMemorySlot
Indicates that an entity possesses a specific memory slot or storage location for holding information or data.
-
C.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
-
D.
hasExternalMemory
Indicates that an entity is associated with or utilizes memory resources located outside its own primary or internal storage.
-
E.
hasComponentDedication
chosen
Indicates that an entity includes or is associated with a specific dedication as one of its components.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:50 a.m.