Triple
T29117026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chula Vistan |
E737074
|
entity |
| Predicate | appliesToCityType |
P90780
|
FINISHED |
| Object | coastal 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: coastal city | Statement: [Chula Vistan, appliesToCityType, coastal city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToCityType Context triple: [Chula Vistan, appliesToCityType, coastal city]
-
A.
appliesToUrbanAreaType
chosen
Indicates that something (such as a rule, measure, or classification) is applicable specifically to a particular type or category of urban area.
-
B.
belongsToCityType
Indicates that one entity is classified under, or associated with, a particular type or category of city.
-
C.
appliesToUrbanArea
Indicates that the relationship, rule, or condition is specifically relevant or applicable to an urban area.
-
D.
cityStatusAppliesTo
Indicates that a particular city status or designation is applicable to a given city or urban entity.
-
E.
appliedToBuildingType
Indicates that something (such as a rule, measure, or classification) is specifically applicable to a particular type of building.
- 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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 28, 2026, 11:23 a.m.