Triple
T3894797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iztapalapa borough hall |
E88142
|
entity |
| Predicate | subdivisionTypeServed |
P36805
|
FINISHED |
| Object | borough of Mexico City |
—
|
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: borough of Mexico City | Statement: [Iztapalapa borough hall, subdivisionTypeServed, borough of Mexico City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionTypeServed Context triple: [Iztapalapa borough hall, subdivisionTypeServed, borough of Mexico City]
-
A.
hasTypeOfSubdivision
chosen
Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
-
B.
servesSuburbsOf
Indicates that a service, route, or facility provides coverage or support to the suburban areas associated with a particular city or region.
-
C.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
D.
isResidentialSuburbOf
Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
-
E.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
- 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_69aed9466d548190939f5217a23ed4ac |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75b5b808190a348a31b1325d3d0 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:21 p.m.