Triple
T3006042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombay Beach, California |
E81903
|
entity |
| Predicate | hasPopulationTrend |
P31774
|
FINISHED |
| Object | small 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: small population | Statement: [Bombay Beach, California, hasPopulationTrend, small population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationTrend Context triple: [Bombay Beach, California, hasPopulationTrend, small population]
-
A.
approximatePopulationTrend
chosen
Indicates an estimated or generalized pattern of how a population changes over time (e.g., increasing, decreasing, or stable) rather than an exact count.
-
B.
populationIncrease
Indicates that the number of individuals in a population has grown over a specified period of time.
-
C.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
D.
hasPopulationStatus
Indicates the current demographic condition or classification of a population associated with an entity.
-
E.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a48f0888190bdec150dac623851 |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad96180eb08190a524c5f458d41382 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.