Triple
T38218276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butterfly Conservatory |
E1010742
|
entity |
| Predicate | approximateNumberOfButterflies |
P201450
|
FINISHED |
| Object | thousands |
—
|
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: thousands | Statement: [Butterfly Conservatory, approximateNumberOfButterflies, thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfButterflies Context triple: [Butterfly Conservatory, approximateNumberOfButterflies, thousands]
-
A.
approximateBatCount
Indicates an estimated number of bats associated with or observed at a given entity or event.
-
B.
hasButterflyPopulation
Indicates that an entity possesses or supports a population of butterflies.
-
C.
approximateNumberOfTulips
Indicates that the relationship specifies an estimated or approximate count of tulips associated with an entity.
-
D.
approximateNumberOfZebra
Indicates that one entity specifies an estimated or approximate count of zebras associated with another entity.
-
E.
hasApproximateNumberOfSwans
Indicates that an entity is associated with an estimated or non-exact quantity of swans.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fff59a00a881909b35b799654b3c45 |
completed | May 10, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69fff4d0a2e081909c972189b33d0128 |
completed | May 10, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69fff59875cc8190864864e951951679 |
completed | May 10, 2026, 3:03 a.m. |
Created at: May 3, 2026, 4:30 p.m.