Triple
T34866204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tumba de Amelia Goyri (La Milagrosa) |
E1005015
|
entity |
| Predicate | seEncuentraEnSección |
P70109
|
FINISHED |
| Object | zona central del Cementerio de Colón |
—
|
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: zona central del Cementerio de Colón | Statement: [tumba de Amelia Goyri (La Milagrosa), seEncuentraEnSección, zona central del Cementerio de Colón]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seEncuentraEnSección Context triple: [tumba de Amelia Goyri (La Milagrosa), seEncuentraEnSección, zona central del Cementerio de Colón]
-
A.
usesSectionOf
Indicates that one entity makes use of a specific section or part of another entity.
-
B.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
C.
isOnSectionOf
chosen
Indicates that one entity is located on, or positioned along, a specific segment or subsection of another entity.
-
D.
operatorInSection
Indicates that an operator is assigned to, works within, or is responsible for a specific section.
-
E.
appliesToSectionOf
Indicates that something is relevant or applicable specifically to a particular section or subsection of a larger whole.
- 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.