Triple
T19124756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosenwald schools program |
E468146
|
entity |
| Predicate | numberOfTeacherHomesBuilt |
P134511
|
FINISHED |
| Object | thousands |
—
|
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: thousands | Statement: [Rosenwald schools program, numberOfTeacherHomesBuilt, thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTeacherHomesBuilt Context triple: [Rosenwald schools program, numberOfTeacherHomesBuilt, thousands]
-
A.
numberOfHouses
Indicates the quantity of houses associated with a given entity or context.
-
B.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
C.
numberOfHousingUnits
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
D.
hasNumberOfHouses
Indicates the quantity of houses associated with a given entity.
-
E.
buildingAlsoHouses
Indicates that a building additionally contains or accommodates another function, entity, or activity beyond its primary purpose.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3cb9d6c81908a8706c1f33a6378 |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:05 p.m.