Triple
T4523035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tirupati district |
E103310
|
entity |
| Predicate | hasForestType |
P57219
|
FINISHED |
| Object | tropical dry evergreen forest |
—
|
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: tropical dry evergreen forest | Statement: [Tirupati district, hasForestType, tropical dry evergreen forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasForestType Context triple: [Tirupati district, hasForestType, tropical dry evergreen forest]
-
A.
hasNearbyForestType
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
B.
hasTrees
Indicates that something possesses or contains one or more trees.
-
C.
hasMajorForest
Indicates that an entity possesses or contains a large, significant forested area.
-
D.
locatedInForest
Indicates that an entity is situated within the boundaries of a forest.
-
E.
hasNationalForest
Indicates that a place or jurisdiction contains, includes, or is home to at least one designated national forest.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd574d7c2481909049955ca47613a6 |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b3e4c88190a7ade3d0ed0ab606 |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:02 p.m.