Triple
T26025200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Cajititlán |
E647268
|
entity |
| Predicate | hasProblemCause |
P708
|
FINISHED |
| Object | untreated wastewater discharges |
—
|
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: untreated wastewater discharges | Statement: [Lake Cajititlán, hasProblemCause, untreated wastewater discharges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProblemCause Context triple: [Lake Cajititlán, hasProblemCause, untreated wastewater discharges]
-
A.
hasCause
chosen
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
B.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
C.
hasProposedCause
Indicates that one entity is suggested or hypothesized to be the cause or explanation for another entity or event.
-
D.
hasCanonicalProblem
Indicates that an entity is associated with, or exemplifies, a standard or canonical problem instance used to represent its core issue or challenge.
-
E.
hasConflictCause
Indicates that one entity is the cause or source of a conflict involving another entity.
- 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_69e77e8b60e88190a3b26c4f0032a2c2 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 22, 2026, 9:05 a.m.