Triple
T12978029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Altos Hills |
E321579
|
entity |
| Predicate | hasUrbanGrowthLimit |
P107877
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Los Altos Hills, hasUrbanGrowthLimit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanGrowthLimit Context triple: [Los Altos Hills, hasUrbanGrowthLimit, true]
-
A.
hasUrbanGrowthCharacteristic
Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
-
B.
hasSuburbanGrowth
Indicates that an area or entity is experiencing or characterized by expansion or development typical of suburban environments.
-
C.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
D.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
E.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
- F. None of above. chosen
Provenance (4 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97f1badac8190a59e60751f47b8d6 |
completed | April 10, 2026, 10:52 p.m. |
Created at: April 9, 2026, 8:38 p.m.