Triple
T2552379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lying-in-state of Elizabeth II |
E56654
|
entity |
| Predicate | queueLengthMaximum |
P40793
|
FINISHED |
| Object | about 10 miles |
—
|
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: about 10 miles | Statement: [lying-in-state of Elizabeth II, queueLengthMaximum, about 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queueLengthMaximum Context triple: [lying-in-state of Elizabeth II, queueLengthMaximum, about 10 miles]
-
A.
frontLineLength
Indicates the total measured extent of the front line where opposing forces or boundaries directly face each other.
-
B.
instructionQueueLength
Indicates the current number of instructions waiting in a queue to be processed.
-
C.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
D.
rideLimit
Indicates a constraint on the maximum number, duration, or frequency of rides permitted for an entity.
-
E.
maxCurrent
Indicates the maximum electric current that is allowed to flow through or be drawn by an entity under specified conditions.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0c8b6f08190a68645db3e8b779a |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd5a1cd508190a660b9a3c6b7cbcb |
completed | March 7, 2026, 7:37 a.m. |
Created at: March 6, 2026, 9:48 p.m.