Triple
T38427182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angangueo |
E903391
|
entity |
| Predicate | typicalFloraFauna |
P111243
|
FINISHED |
| Object | mariposa monarca |
—
|
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: mariposa monarca | Statement: [Angangueo, typicalFloraFauna, mariposa monarca]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFloraFauna Context triple: [Angangueo, typicalFloraFauna, mariposa monarca]
-
A.
notableFaunaRegion
Indicates that a region is known for or characteristically associated with particular notable animal species.
-
B.
faunaDiversity
Indicates the variety and richness of animal species present within a given area or ecosystem.
-
C.
typicalWildlifeObserved
chosen
Indicates that certain wildlife species are commonly or characteristically observed in a given area or context.
-
D.
faunaCharacteristic
Indicates that an entity has a specific trait, feature, or quality related to animals or animal life.
-
E.
fauna
Indicates that an entity is an animal or part of the animal life associated with a particular place or context.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.