Triple
T572858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania |
E13698
|
entity |
| Predicate | hasOfficialFlower |
P317
|
FINISHED |
| Object | Mountain laurel |
—
|
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: Mountain laurel | Statement: [Pennsylvania, hasOfficialFlower, Mountain laurel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialFlower Context triple: [Pennsylvania, hasOfficialFlower, Mountain laurel]
-
A.
hasOfficialStateFlower
chosen
Indicates that a political entity is formally designated as having a particular flower as its official state symbol.
-
B.
nationalFlower
Indicates that a particular flower is officially designated as the national flower of a country or region.
-
C.
hasBirthFlower
Indicates that one entity is the designated birth flower associated with another entity (typically a person or birth date).
-
D.
designatedStateFlowerYear
Indicates the year in which a particular state officially designated a specific flower as its state flower.
-
E.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b49bad88190bc73d31a317c0ef4 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.