Triple
T12677355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linha do Tua |
E302850
|
entity |
| Predicate | impactOfDam |
P103390
|
FINISHED |
| Object | submergence of part of the alignment |
—
|
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: submergence of part of the alignment | Statement: [Linha do Tua, impactOfDam, submergence of part of the alignment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOfDam Context triple: [Linha do Tua, impactOfDam, submergence of part of the alignment]
-
A.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
B.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
C.
infrastructureDamage
Indicates damage or destruction affecting physical infrastructure such as buildings, roads, utilities, or other constructed facilities.
-
D.
impactOutcome
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
E.
isMajorDamOf
Indicates that one dam is the primary or most significant dam associated with a particular river, reservoir, or water system.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b0d9c88190a05d6cbcb7a1642d |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.