Triple
T3894798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iztapalapa borough hall |
E88142
|
entity |
| Predicate | servesPopulationType |
P17586
|
FINISHED |
| Object | urban population |
—
|
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: urban population | Statement: [Iztapalapa borough hall, servesPopulationType, urban population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPopulationType Context triple: [Iztapalapa borough hall, servesPopulationType, urban population]
-
A.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
-
B.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
-
C.
targetedPopulation
chosen
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
D.
hadPopulationType
Indicates that an entity possessed a particular classification or type of population during a given time or context.
-
E.
supportedPopulation
Indicates that one entity provides assistance, resources, or services to sustain or benefit a specified group of people.
- 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.