Triple
T34045321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sede de la Suprema Corte de Justicia de la Nación en el Centro Histórico de la Ciudad de México |
E873070
|
entity |
| Predicate | situadaCercaDe |
P61362
|
FINISHED |
| Object | Palacio Nacional |
—
|
NE NERFINISHED |
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: Palacio Nacional | Statement: [sede de la Suprema Corte de Justicia de la Nación en el Centro Histórico de la Ciudad de México, situadaCercaDe, Palacio Nacional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: situadaCercaDe Context triple: [sede de la Suprema Corte de Justicia de la Nación en el Centro Histórico de la Ciudad de México, situadaCercaDe, Palacio Nacional]
-
A.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
-
B.
oftenLocatedNear
Indicates that one entity is frequently found in close physical proximity to another entity.
-
C.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
D.
situatedNextTo
Indicates that one entity is located immediately beside another, with no significant separation between them.
-
E.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
- 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_69f349a3363081909cea4c9a848cefe2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:51 a.m.