Triple
T9235450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tree of Peace |
E221924
|
entity |
| Predicate | hasSymbolicElement |
P25306
|
FINISHED |
| Object | white roots of peace |
—
|
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: white roots of peace | Statement: [Tree of Peace, hasSymbolicElement, white roots of peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolicElement Context triple: [Tree of Peace, hasSymbolicElement, white roots of peace]
-
A.
hasSymbolicValue
chosen
Indicates that something holds meaning, significance, or representational value beyond its literal or practical function.
-
B.
containsSymbolicAct
Indicates that one entity includes or incorporates a symbolic action or gesture associated with another entity.
-
C.
hasSymbolicForm
Indicates that one entity serves as the symbolic representation or abstract form of another entity.
-
D.
hasNonLogicalSymbol
Indicates that a given formal system, expression, or language includes at least one symbol that is not part of its logical vocabulary (e.g., not a connective, quantifier, or equality sign).
-
E.
hasSymbolicRelationshipType
Indicates that there exists a symbolic (non-literal) relationship of a specified type between two entities.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf09d42488190b8ccb9c4b62fdda8 |
completed | April 1, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:29 p.m.