Triple
T27638844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pay-to-Witness-Script-Hash |
E696534
|
entity |
| Predicate | storesScript |
P165392
|
FINISHED |
| Object | in witness not in scriptPubKey |
—
|
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: in witness not in scriptPubKey | Statement: [Pay-to-Witness-Script-Hash, storesScript, in witness not in scriptPubKey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storesScript Context triple: [Pay-to-Witness-Script-Hash, storesScript, in witness not in scriptPubKey]
-
A.
addsScript
Indicates that one entity attaches or incorporates a script (code or instructions) into another entity, enabling additional behavior or functionality.
-
B.
usesScriptFor
Indicates that one entity employs or relies on a particular script or writing system for its representation, communication, or operation.
-
C.
scriptCode
Indicates that an entity is associated with a particular writing system or script, identified by a standardized script code.
-
D.
storesInterfaceIn
Indicates that one entity keeps or maintains an interface definition within another entity (such as a container, module, or storage location).
-
E.
script
Indicates that an entity is associated with a written text or code (such as a screenplay, program, or written instructions) that defines its content or behavior.
- 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_69f659355a208190be2609ffc7a9c427 |
completed | May 2, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f65875030881909007c502b7dcc998 |
completed | May 2, 2026, 8:03 p.m. |
Created at: April 27, 2026, 2:25 p.m.