Triple
T15627638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | subjectOf |
E375722
|
entity |
| Predicate | Forest |
P119505
|
FINISHED |
| Object | character analysis of Devs |
—
|
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: character analysis of Devs | Statement: [subjectOf, Forest, character analysis of Devs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Forest Context triple: [subjectOf, Forest, character analysis of Devs]
-
A.
forestDistrict
Indicates that one entity functions as the forest district or forest management administrative unit responsible for the other entity.
-
B.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
-
C.
locatedInForest
Indicates that an entity is situated within the boundaries of a forest.
-
D.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
E.
hasNearbyWoodland
Indicates that one entity is located close to or in the immediate vicinity of a woodland area associated with another entity.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb4301881908c7157227fdf79b6 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:14 a.m.