Triple
T23891711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Frankfurt program |
E600786
|
entity |
| Predicate | estimatedDwellingsBuilt |
P19276
|
FINISHED |
| Object | over 10,000 |
—
|
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: over 10,000 | Statement: [New Frankfurt program, estimatedDwellingsBuilt, over 10,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedDwellingsBuilt Context triple: [New Frankfurt program, estimatedDwellingsBuilt, over 10,000]
-
A.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
B.
numberOfHousingUnits
chosen
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
C.
numberBuilt
Indicates the total count of items or structures that have been constructed or produced.
-
D.
buildingAlsoHouses
Indicates that a building additionally contains or accommodates another function, entity, or activity beyond its primary purpose.
-
E.
approximateNumberOfRooms
Indicates an estimated or not precisely known count of rooms associated with an entity.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cd044708819091102ecc160e1961 |
completed | April 29, 2026, 9:19 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.