Triple
T5585865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parque Tezozómoc |
E146753
|
entity |
| Predicate | hasLakeThatRecreates |
P64909
|
FINISHED |
| Object | geography of the Valley of Mexico |
—
|
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: geography of the Valley of Mexico | Statement: [Parque Tezozómoc, hasLakeThatRecreates, geography of the Valley of Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeThatRecreates Context triple: [Parque Tezozómoc, hasLakeThatRecreates, geography of the Valley of Mexico]
-
A.
usesLakeFor
Indicates that an entity utilizes a lake as a resource or setting for some purpose, activity, or function.
-
B.
hasArtificialLakes
Indicates that one entity possesses, contains, or includes one or more man-made lakes within its area or domain.
-
C.
createsLake
Indicates that one entity causes the formation or existence of a lake in relation to another entity or location.
-
D.
hasMajorLake
Indicates that a geographic region or area contains at least one significant lake within its boundaries.
-
E.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020871a3c8190991f291295cadfa5 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:38 p.m.