Triple
T4565054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shark Valley Observation Tower |
E121887
|
entity |
| Predicate | nearbyEcosystem |
P2064
|
FINISHED |
| Object | freshwater marsh |
—
|
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: freshwater marsh | Statement: [Shark Valley Observation Tower, nearbyEcosystem, freshwater marsh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyEcosystem Context triple: [Shark Valley Observation Tower, nearbyEcosystem, freshwater marsh]
-
A.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
-
B.
nearbyFrontier
Indicates that one entity is located close to a boundary or frontier region associated with another entity.
-
C.
nearbyFeature
chosen
Indicates that one entity is located close to or in the immediate vicinity of another entity.
-
D.
nearbyEnvironment
Indicates that an entity is located in or affected by the immediate surrounding conditions or context of another entity.
-
E.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589cde9081909b84186d700fc463 |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.