Triple
T10786374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 7.0 |
E254460
|
entity |
| Predicate | addsScriptSupport |
P82712
|
FINISHED |
| Object | historic scripts |
—
|
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: historic scripts | Statement: [Unicode 7.0, addsScriptSupport, historic scripts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsScriptSupport Context triple: [Unicode 7.0, addsScriptSupport, historic scripts]
-
A.
addsScript
Indicates that one entity attaches or incorporates a script (code or instructions) into another entity, enabling additional behavior or functionality.
-
B.
scriptSupport
chosen
Indicates that one entity provides or enables scripting capabilities or support for another entity.
-
C.
addsScriptsCount
Indicates the number of scripts that are added in a given context or operation.
-
D.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
E.
hasScriptTool
Indicates that an entity uses, is associated with, or is supported by a particular scripting tool or scripting environment.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732d5422481908d7ab833c6cbc879 |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.