Triple
T12912463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Marsh |
E308893
|
entity |
| Predicate | nativeFauna |
P91594
|
FINISHED |
| Object | slaughterfish |
—
|
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: slaughterfish | Statement: [Black Marsh, nativeFauna, slaughterfish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeFauna Context triple: [Black Marsh, nativeFauna, slaughterfish]
-
A.
fauna
Indicates that an entity is an animal or part of the animal life associated with a particular place or context.
-
B.
faunaNote
Indicates a note or annotation specifically about animals or wildlife associated with an entity or context.
-
C.
faunaCharacteristic
Indicates that an entity has a specific trait, feature, or quality related to animals or animal life.
-
D.
basedOnAnimalNativeTo
Indicates that something is derived from, inspired by, or modeled after an animal that is native to a specified geographic region.
-
E.
notableFaunaRegion
chosen
Indicates that a region is known for or characteristically associated with particular notable animal species.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9719f96248190b746f9d4a468560c |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:41 p.m.