Triple
T10172208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ottoman flag |
E235357
|
entity |
| Predicate | symbolElement |
P92223
|
FINISHED |
| Object | crescent |
—
|
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: crescent | Statement: [Ottoman flag, symbolElement, crescent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolElement Context triple: [Ottoman flag, symbolElement, crescent]
-
A.
symbolText
Indicates that a symbol is associated with or represented by a specific piece of text.
-
B.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
C.
symbolLinked
Indicates a relationship where one symbol is connected or associated with another symbol, typically to show reference, correspondence, or linkage between them.
-
D.
symbolRoot
Indicates a relationship where one symbol serves as the root or base form from which another symbol is derived or structured.
-
E.
symbolNumber
Indicates a relationship where a specific numerical identifier is assigned to or associated with a particular symbol.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9e4e0c819097dceb7bf7757948 |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4fed19d481909d2c7ff1114664b6 |
completed | April 1, 2026, 5:03 p.m. |
Created at: March 30, 2026, 9:10 p.m.