Triple
T7935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American elm |
E156
|
entity |
| Predicate | floweringSeason |
P578
|
FINISHED |
| Object | early spring |
—
|
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: early spring | Statement: [American elm, floweringSeason, early spring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floweringSeason Context triple: [American elm, floweringSeason, early spring]
-
A.
stateFlower
Indicates the official flower designated as the symbolic floral emblem of a particular state.
-
B.
hasOfficialStateFlower
Indicates that a political entity is formally designated as having a particular flower as its official state symbol.
-
C.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
D.
averageAnnualPrecipitation
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
E.
year
Indicates the specific calendar year associated with an entity, event, or fact.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2407916ac8190b76d2e6690efaef3 |
completed | Feb. 28, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69a23fe3a87881909ab95bb3a0b474ec |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a240782e108190b6b60c26b84ae179 |
completed | Feb. 28, 2026, 1:10 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.