Triple
T3845474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huixquilucan |
E93558
|
entity |
| Predicate | hasUrbanAreaCharacteristic |
P29003
|
FINISHED |
| Object | rapidly growing residential zones |
—
|
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: rapidly growing residential zones | Statement: [Huixquilucan, hasUrbanAreaCharacteristic, rapidly growing residential zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanAreaCharacteristic Context triple: [Huixquilucan, hasUrbanAreaCharacteristic, rapidly growing residential zones]
-
A.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
B.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
C.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
D.
hasUrbanGrowthCharacteristic
chosen
Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
-
E.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb77a488190be7fc2a1211f1f2d |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.