Triple
T389148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thuluth script |
E8843
|
entity |
| Predicate | inkType |
P12870
|
FINISHED |
| Object | traditional carbon‑based ink |
—
|
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: traditional carbon‑based ink | Statement: [Thuluth script, inkType, traditional carbon‑based ink]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inkType Context triple: [Thuluth script, inkType, traditional carbon‑based ink]
-
A.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
B.
textType
Indicates the classification of a text according to its type, format, or genre.
-
C.
rinkType
Indicates the specific kind or category of rink associated with an entity (e.g., ice rink, roller rink, practice rink).
-
D.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
E.
titleType
Indicates the specific category or kind of title associated with an entity (e.g., whether it is a main title, alternative title, working title, etc.).
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5988708190aa86d9460cecf050 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ebac09408190be802b96bb203d5f |
completed | Feb. 28, 2026, 1:20 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.