Triple
T2922104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summer Street (Boston) |
E78749
|
entity |
| Predicate | hasOfficeDensity |
P43943
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Summer Street (Boston), hasOfficeDensity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeDensity Context triple: [Summer Street (Boston), hasOfficeDensity, high]
-
A.
numberOfOffices
Indicates the total count of offices associated with a given entity.
-
B.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
C.
populationConcentration
Indicates the degree to which a population is densely gathered or distributed within a specific area or region.
-
D.
hasOfficeCluster
Indicates that an entity is associated with or belongs to a specific group or cluster of office locations.
-
E.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:54 p.m.