Triple
T2980294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles River Park residential complex |
E80491
|
entity |
| Predicate | hasBuildingForm |
P44411
|
FINISHED |
| Object | slab towers |
—
|
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: slab towers | Statement: [Charles River Park residential complex, hasBuildingForm, slab towers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingForm Context triple: [Charles River Park residential complex, hasBuildingForm, slab towers]
-
A.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
B.
hasBuildingFunction
Indicates that a building is used for or serves a particular function or purpose.
-
C.
hasBuildingStatus
Indicates the current condition, classification, or operational state assigned to a building.
-
D.
usesBuilding
Indicates that one entity makes use of, occupies, or operates within a particular building.
-
E.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad999e91788190a2d430dd0600a660 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad9611fc348190a5d17d237f653f60 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.