Triple
T11845908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elder Law Clinic |
E281773
|
entity |
| Predicate | housingArea |
P101824
|
FINISHED |
| Object | landlord-tenant issues |
—
|
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: landlord-tenant issues | Statement: [Elder Law Clinic, housingArea, landlord-tenant issues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: housingArea Context triple: [Elder Law Clinic, housingArea, landlord-tenant issues]
-
A.
roofArea
Indicates the total surface area covered by the roof of a structure.
-
B.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
C.
grossLeasableArea
Indicates the total floor area within a property that is available to be leased to tenants, excluding common or non-leasable spaces.
-
D.
hasCadastralArea
Indicates that an entity possesses or is associated with a specific cadastral (official land registry) area measurement.
-
E.
fareArea
Indicates the geographic or zonal region within which a particular fare or pricing rule applies.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65b5ff08190bb58361f6a6acdca |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.