Triple
T11649808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lying-in-state of George VI |
E276871
|
entity |
| Predicate | coffinContained |
P100180
|
FINISHED |
| Object | remains of George VI |
—
|
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: remains of George VI | Statement: [lying-in-state of George VI, coffinContained, remains of George VI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coffinContained Context triple: [lying-in-state of George VI, coffinContained, remains of George VI]
-
A.
coffinLocation
Indicates the place where a coffin is situated or stored.
-
B.
coffinDrapedWith
Indicates that a coffin is covered or adorned with a particular cloth, flag, or decorative material.
-
C.
coffinLaterBecomes
Indicates that something which is initially a coffin later transforms into or is repurposed as another object or state.
-
D.
numberOfCoffins
Indicates the quantity of coffins associated with a given entity or situation.
-
E.
hasSarcophagusMaterial
Indicates that a sarcophagus is made from, or primarily composed of, a specified material.
- F. None of above. chosen
Provenance (4 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cea9308190a13f7dd995ea07a4 |
completed | April 10, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
| PDg | Predicate description generation | batch_69d87f30642c8190ad94fa061cde186b |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:39 p.m.