Triple
T1948264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiang River basin |
E42102
|
entity |
| Predicate | hasFloodControlInfrastructure |
P25048
|
FINISHED |
| Object | reservoirs |
—
|
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: reservoirs | Statement: [Xiang River basin, hasFloodControlInfrastructure, reservoirs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodControlInfrastructure Context triple: [Xiang River basin, hasFloodControlInfrastructure, reservoirs]
-
A.
hasFloodControlStructure
Indicates that an entity possesses or is equipped with a structure designed to manage, control, or mitigate flooding.
-
B.
hasFloodProtectionInfrastructure
chosen
Indicates that there exists built or implemented infrastructure designed to protect against or mitigate flooding for the referenced entity.
-
C.
hasFloodProtectionProject
Indicates that a flood protection project exists or is implemented for the referenced entity.
-
D.
hasFloodHistory
Indicates that the subject has experienced one or more flood events in the past.
-
E.
hasGlobalInfrastructure
Indicates that an entity possesses infrastructure, facilities, or operational capabilities that are distributed across multiple countries or regions worldwide.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb33040c881908f42e80cbe1b1aca |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff25a588190bb4cbc8df9fc6d64 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.