Triple
T27638851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pay-to-Witness-Script-Hash |
E696534
|
entity |
| Predicate | witnessProgramLength |
P162786
|
FINISHED |
| Object | 32 bytes |
—
|
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: 32 bytes | Statement: [Pay-to-Witness-Script-Hash, witnessProgramLength, 32 bytes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: witnessProgramLength Context triple: [Pay-to-Witness-Script-Hash, witnessProgramLength, 32 bytes]
-
A.
witnessCount
Indicates the number of distinct witnesses associated with a particular event, action, or relationship.
-
B.
instructionLength
Indicates the duration or amount of time required to carry out a given instruction or operation.
-
C.
proofSize
Indicates the size or length of a proof associated with an entity, typically measured in steps, symbols, or overall complexity.
-
D.
scriptCodeLength
Indicates the length or number of characters in a given script or code sequence.
-
E.
maximumProgramSize
Indicates the largest allowable or observed size of a program within a given context or system.
- 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_69ef5909f3848190805f35b76833e722 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6318fec0c8190971b4fc1a7df10d3 |
completed | May 2, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d14c24c81909e86678c1b5fd429 |
completed | May 2, 2026, 4:57 p.m. |
Created at: April 27, 2026, 2:25 p.m.