Triple
T14806216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Khabarovsk Krai |
E348042
|
entity |
| Predicate | greenStripeSymbolism |
P32538
|
FINISHED |
| Object | taiga forests |
—
|
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: taiga forests | Statement: [Flag of Khabarovsk Krai, greenStripeSymbolism, taiga forests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenStripeSymbolism Context triple: [Flag of Khabarovsk Krai, greenStripeSymbolism, taiga forests]
-
A.
greenStripeMeaning
Indicates that something has a stripe colored green or marked with green striping.
-
B.
greenStripeRepresents
chosen
Indicates that a green stripe symbolically stands for or denotes a particular meaning, status, or attribute in a given context.
-
C.
goldStripeSymbolizes
Indicates that a gold stripe is used as a symbol representing a particular quality, status, achievement, or meaning in relation to something else.
-
D.
blackStripeSymbolism
Indicates the symbolic meaning or thematic significance associated with a black stripe in a given context.
-
E.
redStripeMeaning
Indicates that something has a red-colored stripe and conveys the meaning, symbolism, or significance associated with that red stripe.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf32666081908e84f985c47eb963 |
completed | April 14, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:35 a.m.