Triple
T5068061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mountain House |
E114191
|
entity |
| Predicate | originalPlanHousingUnits |
P19276
|
FINISHED |
| Object | approximately 15,000 |
—
|
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: approximately 15,000 | Statement: [Mountain House, originalPlanHousingUnits, approximately 15,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalPlanHousingUnits Context triple: [Mountain House, originalPlanHousingUnits, approximately 15,000]
-
A.
originalPlan
Indicates that one entity is the initial or primary plan or intended course of action associated with another entity.
-
B.
numberOfHousingUnits
chosen
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
C.
originalUrbanPlanBy
Indicates that an urban plan was initially conceived or designed by a particular agent (such as a planner, architect, or organization).
-
D.
hasHousingUnits
Indicates that an entity possesses or contains a specified number or set of housing units.
-
E.
plannedAffordableUnitsShare
Indicates the proportion of all planned housing units in a project or area that are designated as affordable units.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd749dd1a08190858fa739df024eb4 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.